{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  },
  "orig_nbformat": 4,
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.8.3 64-bit ('base': conda)"
  },
  "interpreter": {
   "hash": "dca0ade3e726a953b501b15e8e990130d2b7799f14cfd9f4271676035ebe5511"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "import numpy as np\n",
    "import random"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "def CTV(a):\n",
    "    l=len(a)\n",
    "    b=np.zeros((l,1))\n",
    "    for i in range(l):\n",
    "        b[i]=int(a[i])\n",
    "    return b\n",
    "\n",
    "def ARK(a,b):\n",
    "    c=np.mod(a+b,2)\n",
    "    return c\n",
    "\n",
    "def SR(a):\n",
    "    t=a[9:12]\n",
    "    a[9:12]=a[3:6]\n",
    "    a[3:6]=t\n",
    "    b=a\n",
    "    return b\n",
    "\n",
    "def RN(a):\n",
    "    t=a[3:6]\n",
    "    a[3:6]=a[0:3]\n",
    "    a[0:3]=t\n",
    "    b=a\n",
    "    return b\n",
    "\n",
    "def MC(a):\n",
    "    A=np.eye(3)\n",
    "    B=np.array([[0,1,0],[1,0,1],[1,0,0]])\n",
    "    M1=np.hstack((A,B))\n",
    "    M2=np.hstack((B,A))\n",
    "    M=np.vstack((M1,M2))\n",
    "    a[0:6]=np.mod(np.dot(M,a[0:6]),2)\n",
    "    a[6:12]=np.mod(np.dot(M,a[6:12]),2)\n",
    "    b=a\n",
    "    return b\n",
    "\n",
    "def SB(a):\n",
    "    l=len(a)\n",
    "    b=np.zeros((l,1))\n",
    "    A=np.array([[1,0,1],[1,1,0],[0,1,1]])#S盒中的仿射变换\n",
    "    s=np.array([[1],[0],[1]])\n",
    "    for i in range(int(l/3)):\n",
    "        b[3*i+2]=np.mod(a[3*i+1]+a[3*i]+a[3*i+2]+a[3*i+1]*a[3*i],2)\n",
    "        b[3*i+1]=np.mod(a[3*i+2]*a[3*i+1]+a[3*i],2)\n",
    "        b[3*i]=np.mod(a[3*i+2]*a[3*i]+a[3*i+1]+a[3*i],2)\n",
    "        b[3*i:3*i+3]=np.mod(np.dot(A,b[3*i:3*i+3])+s,2)\n",
    "    return b"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "#GF(2^3)上的不可约多项式为x^3+x+1\n",
    "def Ss_AES():\n",
    "    data = np.zeros((2**12, 12))\n",
    "    R1=np.zeros((6,1))\n",
    "    R1[0]=1\n",
    "    R2=np.zeros((6,1))\n",
    "    R2[0]=1 #子秘钥生成过程中的两个已知比特串\n",
    "    P=CTV('{:012b}'.format(random.randint(0,2**12-1)))\n",
    "    for j in range(2**12):\n",
    "        K=CTV('{:012b}'.format(j))\n",
    "        C=MC(SR(ARK(P,K)))\n",
    "        K1=np.mod(K[0:6]+R1+SB(RN(K[6:12])),2)\n",
    "        K2=np.mod(K1+K[6:12],2)\n",
    "        K=np.vstack((K1,K2))\n",
    "        C=SR(SB(ARK(C,K)))\n",
    "        K1=np.mod(K[0:6]+R2+SB(RN(K[6:12])),2)\n",
    "        K2=np.mod(K1+K[6:12],2)\n",
    "        K=np.vstack((K1,K2))\n",
    "        C=ARK(C,K)\n",
    "        data[j,:]=C.T\n",
    "    return data"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "# f is a function; x0 is a N-dimention row vector; xerr is a const\n",
    "def NM(f,x0,xerr):\n",
    "    N=len(x0)\n",
    "    times=0\n",
    "    x=np.zeros((N+1,N))\n",
    "    y=np.zeros(N+1)\n",
    "    x[0,:]=x0\n",
    "    for ii in range(N):\n",
    "        x[ii+1,:]= x[0,:]\n",
    "        if x[0,ii]==0:\n",
    "            x[ii+1,ii]=0.00025\n",
    "        else:\n",
    "            x[ii+1,ii]=1.05*x[0,ii]\n",
    "    for ii in range(N+1):\n",
    "        b=x[ii,:]\n",
    "        y[ii]=f(b)\n",
    "        times=times+1\n",
    "    for kk in range(10000):   \n",
    "        order=sorted(range(len(y.T)),key=lambda g: y[g])\n",
    "        x=x[order,:]\n",
    "        if np.linalg.norm(x[N,:]-x[0,:])< xerr:\n",
    "            break\n",
    "        m=np.mean(x[0:N-1,:])\n",
    "        r=2*m-x[N,:]\n",
    "        f_r=f(r)\n",
    "        times=times+1\n",
    "        if y[0] <= f_r and f_r < y[N-1]:\n",
    "            x[N,:]=r\n",
    "            y[N]=f_r\n",
    "            continue\n",
    "        if f_r<y[0]:\n",
    "            s=m+2*(m-x[N,:])\n",
    "            f_s=f(s)\n",
    "            times=times+1\n",
    "            if f(s)<f_r:\n",
    "                x[N,:]=s\n",
    "                y[N]=f_s\n",
    "            else: \n",
    "                x[N,:]=r\n",
    "                y[N]=f_r\n",
    "            continue\n",
    "        if f_r<y[N]:\n",
    "            c1=m+(r-m)*0.5\n",
    "            f_c1=f(c1)\n",
    "            times=times+1\n",
    "            if f(c1)<f_r:\n",
    "                x[N,:]=c1\n",
    "                y[N]=f_c1\n",
    "                continue\n",
    "        else:\n",
    "            c2=m+(x[N,:]-m)*0.5\n",
    "            f_c2=f(c2)\n",
    "            times=times+1\n",
    "            if f(c2)<y[N]:\n",
    "                x[N,:]=c2\n",
    "                y[N]=f_c2\n",
    "                continue\n",
    "        for jj in range(1,N+1):\n",
    "            x[jj,:]=x[0,:]+(x[jj,:]-x[0,:])*0.5\n",
    "            y[jj]=f(x[jj,:])\n",
    "    return x[0,:],f(x[0,:]),times"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "e0=[[1],[0]]\n",
    "e1=[[0],[1]]\n",
    "data=Ss_AES()\n",
    "n=np.size(data,1)\n",
    "cipher=data[random.randint(0,2**n),:]\n",
    "Ss=np.zeros((2**n,2**n))\n",
    "for i in range(2**n):\n",
    "    ds=1\n",
    "    for j in range(n):\n",
    "        if data[i,j]==0:\n",
    "            ds=np.kron(ds,e0)\n",
    "        else:\n",
    "            ds=np.kron(ds,e1)\n",
    "    Ss[:,i]=ds.T"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "g=nx.random_regular_graph(11,12,seed=7)\n",
    "list(g)\n",
    "nx.draw(g,with_labels=True,font_weight='bold')"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": 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YkyZNYmZmZr77aWlpbNq0Kbt06cKcnJxi5S1fvpy9evUiSfr6+uZTojKZjGKxON/gL5FI+NVXX3Hnzp0FZJ05c4YVK1akubk579y5U6LnuXTpEtu1a0dra2uuXLmyRH0uT968ecNjx45x1qxZbNu2LcViMS0tLRkQEMD58+czOjqa6enp8vIpKSnct28fx44dS29vb+rp6bF+/foMDQ1lZGRksRZwceTl5XHr1q10c3Ojp6cn9+7dW6SF+OLFC9asWZP+/v4KJyF5eXnU0tLi8uXLGRYWxunTpxeQ0bRpU27YsCHftcOHD1MsFvPUqVMl6ndaWhqXLVvGatWq0cPDgxs2bPgikxuBvw+C4hMoFYmJifT19WX9+vV59erVAvdfvXrFunXrcuDAgYVaA5/i5+fHiIgIkqS1tTUfPHiQ776/vz93796d79pvv/3GKlWqyN1nHxMTE0N9fX2amJjwypUrJXwyMjY2lq1bt6adnR3XrVuncpdjaZHJZLx37x63bdvG4cOH08PDgxUqVKCpqSlNTExYoUIFenl5ccqUKTx+/Hg+pVgWcnJyuH79ejo5OdHX15dHjhwp1nJ6+vQpXV1d2bNnT5qZmfHGjRsFypw8eZLq6up8+fIlQ0JCuHTpUoVlnJycmJeXl+/6iRMnKBaLefTo0RI/h1Qq5aFDh9i6dWuamZlx8uTJ/PPPP0tcX+Dfg6D4BJQiOzub06ZNo0gk4rJlyxQqtSdPntDNzY3ff/99iV1Lb968oYGBAd+9e8ecnBxqa2sXGOymTJnCiRMnFqj79ddfc9GiRQrlxsXF0dDQkJUqVeK5c+dK1JcPnDlzhs2aNaOjoyM3bdpUYgVeHshkMiYmJnLNmjXs1asX7e3tKRKJ2LZtW4aEhHDUqFHs0qULHRwcaGRkxJYtW3LKlCk8ePBgqS29rKwsLl++nLa2tmzZsiWjo6NLVC8pKYlVq1bl0KFDKRaL+fvvvyss17NnT5qbm5Mke/XqxU2bNil8bl9fX27ZsqXAvdOnT1MsFvPAgQNKPNV7EhMTGRwcTCMjI3bv3p0xMTFKyxD45yIoPoESc+bMGbq6urJ9+/ZMSkpSWObOnTt0cHDg3LlzlZK9fft2+vv7y2XY29sXKLN//376+fkVuH7z5k2ampoWOsAnJCTQ2NiYBgYGSlkIHzh58iR9fHzo7OzM7du3KxUAUlry8vJ44cIFLlq0iB06dKCpqSnt7OwYGBjI1atXFxmI8uLFC+7bt48TJ05k8+bNaWhoSCcnJwYGBnLZsmWMi4sr0o377t07Lly4kJUrV2b79u0ZGxtb4n7fv3+fDg4OnDhxIq2srBS6oT9gZmbGnj17kiTbtWvHvXv3Kix37NgxOjs7K5x4xMbG0szMrIAnoKSkpqZy0aJFdHBwYP369blt27Yv7uIWKH8ExSdQLG/evOHgwYNpaWnJnTt3FmrFXblyhZaWlly1apXSbXTr1k1e79ixY2zSpEmBMs+ePaOxsbHC9gcPHsyRI0cWKv/atWsUiUQ0MDCQu1OVQSaT8ejRo6xfvz6rV6/OiIgIlSrAjIwMnjhxgtOnT2eLFi1oYGDA6tWrc/Dgwdy6dWuhE42SIJFIeP36da5bt44DBgygu7s79fT02KBBA44aNYq//PILHz16xNTUVM6aNYtmZmbs0qULL1++rFQ7t2/fpq2tLefNm0cXFxeFrssPJCUlUVNTk4cPHyb5fk23MItSJpPR29ub27dvV3g/Pj6e5ubm3LFjh1L9/RiJRMLIyEg2bdqUlpaWnDlzJl+8eFFqeQJ/bwTFJ1Aku3fvppWVFQcOHFjkVoRz587RzMys0MGpKHJycmhkZCRfb1mzZg2/++47hWWtra159+7dAtdfvHhBkUhUZCDLzZs3KRaLWalSJa5fv17pfpLvB+EDBw6wdu3arFWrFvft21eqSMGPA1G8vLzkgShjxozh3r17yxyIUhxpaWk8ceIE58yZw9atW7NixYpUU1OjjY0NR40axZMnT/Ldu3cllnfz5k1aWVlx+fLlbNiwIceMGVNk+fDwcGpqasqDTNzd3Ytch42KiqKbm1uhk42rV6+ycuXKCt2lynL16lX279+fRkZGDAoKYkJCQpllCvy9EBSfgEKePHnCDh060NnZudi1naNHj9LU1JQHDx4sVVvHjh1jvXr15O8nTpzIGTNmKCzboUOHQmf2c+bMYUBAQJFt3bp1ixYWFjQxMSl0XbAkyGQy7tmzh+7u7vT09GRUVFSRCjApKYlbt27l4MGDWb16derr67NFixacPn06T5w4obJAFGV49uwZx4wZQxMTEw4cOJC///47d+zYwVGjRsmjQmvWrMkBAwZw/fr1vH79ukLFc+XKFVauXJkbNmxgQEAAu3fvXqw17OnpyRo1asjf29jYFLm9QiaT0dPTs0jXaWJiIq2trblmzZoSPH3xvHr1inPnzqW1tTV9fX0ZERFRYN1Z4J+JoPgE8iGVSrlixQqamppy6tSpCqMlPyYiIqLIAIaSMGzYMM6ePVv+vnv37ty8ebPCsrNnz2ZoaKjCe5mZmbS1tS22L3fv3qWVlRXNzMw4adKkMu3tkkql/PXXX+nq6soGDRrw+PHjlMlkvHnzJlevXs3AwEDa2dnR1NSUHTp04KJFi3jhwoUvGin66NEjDh06lMbGxhwxYkSh+wNzcnJ44cIFLlu2jD179qSjoyMNDQ3ZvHlzTpo0ifv37+dvv/1Gc3Nzbt++ncOGDWPTpk2L/c1kZWVRS0uLU6dOlV8zMDDg27dvi6y3f/9+1qxZs0ileufOHdrZ2XHZsmVFylKG3Nxc/vrrr2zYsKHclftxggaBfx6C4hOQc/36dXp7e7Nhw4YKw88/5aeffqKFhQXj4+NL3aZMJqONjQ2vXbsmv+bt7c3Tp08rLH/kyBE2bty4UHk///wzPT09i7U4Hjx4QFtbW1pbWzM4OLhM63V5eXk8f/48e/TowYoVK1JLS4vm5ubyQJSbN2/+LTZO37lzh/369aOJiQm///57Pn/+XGkZr1694oEDBxgWFsZ69epRTU2N5ubm/Oqrr1i5cmX+9ttvxSq+qKgo6ujo8NKlSyTff34aGhrFfgcymYweHh7cs2dPkeUePHjAKlWqcOHChco9XAm4ePEie/fuTSMjIw4cOJDXr19XeRsC5Y+g+ASYlZXFsLAwmpqa8scffyyREli8eDFtbW35xx9/lKnthIQEVqlSJZ9isLCwKNQKSUlJoYGBQaFbC6RSKevWrcutW7cW23ZSUhIdHBzo4ODAHj16lNgKy8jI4PHjxzlt2jR5IEqNGjU4ZMgQbtmyRR4l6OfnVyCl2pfgxo0b7Nmzp9yKV4W18vvvv1MsFnPfvn2cN28eRSIRAwMDWatWLfl65YgRI7ht2zbev38/3/cbFBTEihUryn9nKSkpNDY2LlG7e/bsoYeHR7ETicePH7Nq1aqcNWtW6R+yCJ4/f85p06bRwsKCzZs35759+z5LtK+AahAU33+c6OhoOjs7MyAgoETpvWQyGSdPnsxq1aqpJAfitGnTOGrUKPn7zMxMVqhQochBpEqVKkVapNHR0bSzsytRdo4nT56watWqrFatGtu2bVsg+wz5fmDeu3cvx4wZw/r161NPT49eXl4cO3Ys9+3bp1CR5OTkcPXq1bSxsaG/vz8vXrxYbF9UzaVLl9ipUyeamZlx7ty5xboSS8rx48dpamrKo0eP8tixYzQzM8tn+aSnpzM6Oprz5s1jx44dWblyZYrFYrZr146zZs1ipUqV2Lx5c3n5e/fu0cHBoURtS6VS1qxZk/v37y+27NOnT+nm5sbJkyeXm8Wdk5PDLVu2sG7dunR0dGR4eLjKPmeB8kNQfP9RXr9+zf79+9PKyqpY19EHpFIphw0bxlq1aqks1PtDUuoPJCYm0snJqcg6Xbt2LTZ6r0OHDvzhhx9K1Idnz57R1dWV1atXZ+PGjXnjxo18gSgGBgb08/OTB6Iok8w6Ozuby5cvp6WlJTt06KBUBpnScu7cOfr7+9PS0pLh4eEqDZyJioqiqakpT506xYSEBIrF4mKDn2QyGZOSkrhz504GBQVRXV2d2trarF69Ovv168dJkybRxcWlxAkCdu7cyXr16pVImb18+ZJfffUVx44dW67uZplMxnPnzrFr1640NjZmSEgIb926VW7tCZQNQfH9x5DJZPz1119ZuXJlBgcHF0gaXBgfn7BQ0jrF8XFS6g9ERUUp3KT+MQsWLOCwYcOKLHPr1i2KRCK+fPmyyHIymYw3btzgggULWKlSJWppaVFDQ4P+/v5cvHgx4+LiVBLJl5mZycWLF9Pc3JydO3cu0RqqMshkMp44cYLNmjWjvb09f/zxR5Xno9y7d688QfTDhw9pZWXFX3/9VSkZ8+fPp46ODu/du8f4+HiuWLGCLVq0oK6uLg0MDNi0aVOOHz+ekZGRfPbsmUIZUqmUbm5u8j2AxZGSksI6deowJCTks6y1Pn78mBMnTqRYLKa/v3+JUrwJfF4ExfcfIikpiW3btqWbm1uJstt/ICsri+3atWObNm1UenTPx0mpP7By5UoOGDCgyHqnTp2il5dXsfKHDx/O4ODgfNdyc3MZGxvLhQsX8ptvvqFIJKK9vT179erFxYsX08XFhZ6ennRxcSnTpvHCSE9P57x58+RZS8pqFchkMh46dIgNGjRgtWrVuHHjxnKJGN25cyfNzMwYFxfHlJQUuri4cMmSJUrLqVu3Lq2srPJd27VrFzt27MiUlBRGRUVx6tSpbN26NY2NjWlnZ8euXbty8eLFPHfunFyZb9++nd7e3kqlxPP29ubAgQM/21pcZmYm169fz5o1a9LFxYUrV65Uam+kQPkhKL7/ABKJhEuXLqVIJOLMmTOVSsn09u1bNmnShF27dlV5KqePk1J/YNy4cZwzZ06R9dLS0qinp1fsAJ+cnEyRSMSffvqJ06ZNY/Pmzamvry8PRNm2bVuBIJrXr1/T09OTDRo0oJ2dHW/fvl26hyuGtLQ0zpw5k6ampgwKCuK9e/eUqi+VSrl7927Wrl2bNWrU4I4dO8otl+jPP/9MCwsLXr58mZmZmSXaoK6It2/fUltbm4MGDcp3ff369QoTFshkMt66dYubNm1icHAwa9euTT09PXp6ejI4OFi+Yb2kyi8tLY2NGjVinz59PmveVZlMxlOnTrFjx44UiUQMDQ0tkIBd4PMiKL5/OVeuXGG9evXYqFEjpSMwP5ywMGjQIJUPFB8npf6Yzp07c9u2bcXWd3V1VZhRIzk5mZGRkQwNDWW9evWopaVFY2Njjhs3jvv37+fr169L1Ddvb282btyYlStXLtfMHampqZwyZQpFIhEHDBhQbMDQh6OBqlevzrp16zIyMrJcLZj169fT0tKSN27coEQiYUBAALt161aqNiMiIigSiRgZGZnv+qJFi/IFOBVFRkYGT58+zQULFtDT05Pa2toUiUT8+uuvOWPGDB49erTIDEMZGRls0aIFu3Xr9kX2Uj548IBjxoyhSCRihw4dePLkScEN+gUQFN+/lMzMTE6YMIFisZhr165VeqB68uQJXV1dOX78+HL5j/lxUuqP8fT0LNEWgN69e3PNmjV89OgRf/75Zw4aNIhubm7yQJQZM2bw5MmTfP36NR0cHHj8+HGl+peWlkYfHx82bdqUYrG40H2FqiIlJYUTJkygiYkJhw4dWiDCNjc3V340kI+PDw8fPlzuA+aPP/5IGxsb3rp1izKZrMQb1AujV69erFChQoE14sLO4iuOvLw8Ojk5cefOndy1axfHjRvHRo0aUV9fn66urgwKCuKqVauYkJCQb502KyuL/v7+DAgI+GIJqdPT07ly5Uq6uLiwZs2aXLduncKIYoHyQVB8/0KOHz9OJycndunSpdAAgaL4cDpCSaMiS8PHSak/xtTUtNA+fwhEWbVqFevWrUt9fX2KxWIGBAQwPDy80ECUX375hR4eHkor//T0dDZt2pTNmjWjqakpo6KilKpfGl68eMHQ0FAaGxtz5MiRfPjwIVesWEE7Ozv6+fmV+GigshIeHk57e3u5C3bevHl0d3cvdWCTVCqlkZERa9euXeBeYWfxlYQNGzawWQXlmgsAACAASURBVLNm+a7l5eUxISGBq1atYlBQEF1cXKivr89GjRpx3Lhx3L17N+/fv88OHTrw66+//qKH0spkMh45coRff/01xWIxJ0yYUOgeVgHVISi+fxHJycn87rvvaGNjw3379pVKxocTFlavXq3i3v3Fp0mpP/Du3Tvq6urKLZnc3FzGxMRwwYIFbN++PUUiER0cHNi7d2+OHz+ebm5uJbJ6PmT337hxo9J9zcjIoJ+fH1u0aEEzM7MynQCgDHfv3qWPjw/V1NTo6OhY4ghGVfDDDz/QyclJ7nb9+eefFZ6grgxxcXE0NjbOl6bsA7169SrVd0O+/404ODgUa5GnpqbyyJEjnDFjBv39/SkSiWhtbU1ra2tWq1aNx44d++IW1+3btxkSEkJjY2N26dKFZ8+eFdyg5YSg+P4FyGQybtu2jRYWFhw+fDjT0tJKJefDCQvlPbh/mpT6A7GxsbS1teXUqVPZrFkz6uvr093dncHBwdy+fXu+gTczM5O6urolnq2fO3eO1tbWpYpKzcrKYps2bdiiRQtaWlqqLAmyIt68ecPZs2fTzMyMnTt35uHDhzl48GCamJhw0qRJJVqjLC0ymYzTpk2ji4uLfFLy22+/FdigXhqmTZtGsVjMM2fOFLjXrl27Aut+yrB27Vq2bNlSqToymYx37tzhpk2b6OzsTAMDA+rq6rJ27doMDg7mpk2b5C7ez83bt2+5ZMkSOjo6sm7duty8eXOp3csCihEU3z+cBw8esE2bNnR3dy/TKdJHjhyhqakpDx06pMLeKeZDUupPA1EqVKhAIyOjEgei1KpVS6ln7tKlS6GnPhRHdnY227Vrx+bNm9POzo7z5s0rlZzCSE5OZlhYGEUiEXv16sWbN2/mu//gwQP269ePIpGI06ZNU9leyg/IZDJOmDCBNWrUkOfwvHz5cok2qJcEDw8PVqxYUWFAia+vb74kBsqSk5NDW1vbUqeHk0gk7N+/P728vHj06FEuXryYXbp0oZ2dHY2Njdm6dWtOmzaNUVFRnzU5tVQq5f79+9miRQtaWFhw2rRppVq6ECiIoPj+oeTl5XHRokUUiUScM2dOmSLUdu7c+VkCOB4+fMjNmzezYsWKrFKlCg0NDdmyZUvOnDmTp06d4qJFizhkyJASy+vfvz+XL19e4vL37t2jiYkJnz59WpruMycnhwEBAWzWrBldXFxUEvjz7Nkzjh07Vn40UHHbGu7cucPevXtTLBZzzpw5KtkXJpPJOGrUKHp4ePDVq1ckWeoN6op48eIFdXV12bZtW4X33d3dlT709lN+/PFHhcFSJUUqlXLo0KH09PTMN+F69uwZIyMjOX78eDZt2pQGBgasVq0ae/fuzRUrVjA+Pv6zRIfeuHGDgwYNopGREXv16vVFUuD9mxAU3z+QS5cusU6dOmzWrFmZ95mtX7+eFhYW8kz5qkIqlfL69ev88ccf2aNHD9rY2FAsFrNZs2YUiUQKA1FGjRrF+fPnl7iN1atXs0+fPkr1KzQ0tNgN8kWRm5vLrl27snHjxqxdu3apt3okJSVx2LBhNDY25vDhw5XeLJ+YmMhu3brRzMyMCxYsKHViAalUyiFDhrBevXryAT8lJYWurq6l2qCuiI0bNxZ5VJCNjQ0fPnxYpjays7NpbW3NuLi4UsuQyWQcPXo0a9WqJZ8AfIpEIuHVq1e5Zs0a9uvXj9WrV2fFihXp4+PD0NBQ7ty5s1yDU1JSUjh//nza2tqyQYMG/OWXX77oEVf/VATF9w8iIyODY8eOpZmZGTds2FBma2PRokW0s7NTSU7BTwNRTExMWKVKFfbp04fr1q2Tr5d8mpT6Yzp27KiUhREfH8/q1asr1c/Xr1/TzMws3zFIypKXl8fAwED6+vrS19dXqc39d+/eZf/+/WliYsJx48aV6migj7l27RoDAgJYuXJlLl26VKkIRYlEwn79+rFhw4byxMpZWVnyQVxVfPvttzQxMWFiYqLC+wYGBipx3S5btozt27cvkwyZTMaJEyeyevXqJf5u3r59y99++42zZs1iu3btKBaLaWlpyYCAAM6bN4/R0dEqP2g4Ly+Pu3btYqNGjWhtbc05c+YUqqwFCiIovn8IR48eZZUqVdi9e/cyJ4iWyWScNGkSnZ2dS52WKz09nceOHcsXiFKzZk0OHTqUO3bsKDQC8NOk1B9Tq1YtpWbsOTk51NPTU9rdt3TpUrZq1UqpOp8ikUgYFBTEhg0b0t/fv9h0bjdu3GBgYCBFIhGnTJnC5OTkMrX/KZcuXWK7du1obW3NlStXFquIPyjvpk2byj8/iUTCTp06lXqDuiJyc3NpYGBAS0tLhRO1vLw8qqurq6S9rKwsWlpaqsR7MWPGDDo7O5cqklUmk/H+/fvctm0bR4wYIT/Ro1atWhw0aBA3bNjAmzdvquwzvnTpEr/77jsaGRmxX79+nyUR+j8dQfH9zXn16hV79epFOzs7lQSefFjL8PDwUEqBvnr1inv27OHo0aPp6elJPT09NmjQgN9//z0PHDhQomhDRUmpP8bIyEjpWWu9evWUPv09JyeHVatWLfMWAalUygEDBrB+/frs0qWLwgTeCQkJ/Pbbb2lmZsY5c+aoPCjlU2JjY9m6dWva2dlx3bp1Ct1gubm57Ny5M1u1aiUP4ZfJZAwJCSnTBnVFnDp1ijY2NgpTkpHvXXdGRkYqay88PJwBAQEqkTVv3jw6OjqW2Q1LvnfFxsTEcMmSJezevTsdHBxoZGREPz8/hoWF8eDBg2W22F6+fMmZM2fS0tKSTZo04Z49ez5rarZ/EoLi+5sik8m4efNmmpubc/To0SoJYsjNzWXPnj3p6+tb7AD88OFDbtmyhQMHDqSrqysNDQ3ZqlUrzpo1i6dOnSrVnqdly5YVSEr9gdTUVOrr6yvtvh06dCgXLVqkdF/27NnDGjVqlHlg+DgoYsCAAfIjm86fP8+vv/6alpaWXLx4scpdXcVx5swZNmvWjI6Ojty0aZP8ObOzs/nNN9+wXbt2+dyi8+fPp7u7e5HpvkrD2LFjWa1atULT0N27d4/29vYqay8jI4MWFha8evWqSuQtXbqU9vb2vHv3rkrkfcyLFy+4b98+Tpo0ic2bN6ehoSGdnJzYs2dPLlu2jBcuXChVZpmcnBxu27aNXl5etLe358KFC8v8vb56l80fT93liB2X+N3GCxyx4xJ/PHWXye/+mdssBMX3N+TevXv08/NT2vVXFJmZmWzXrh39/f0LuOSkUimvXbvGlStXsnv37rSxsaGZmRk7derEJUuWMD4+XiVH8yhKSv2BhIQEuru7Ky1zw4YN7N69u9L1ZDIZfX19VbInTyaTceTIkaxVqxa7dOlCPT09ucvxS2YFIcmTJ0/Sx8eHzs7O3LRpE1u3bs1OnTrlG1C3bt1KW1vbcgnKcHV1pb6+fqHehfj4eNaqVUulbS5YsIBdunRRmbxVq1bR2tpa6Vy3yiKRSHj9+nWuX7+eAwYMoLu7O/X09Ojt7c1Ro0Zxx44dfPjwoVKTw9jYWPbo0YNGRkYcMmRIoeushXE5KZUDNsex2uRDrDb5EO3GH5C/nP93beCWOF5OUu2EqbwRFN/fiLy8PM6bN48ikYjz589XWbTW27dv2bhxY3br1o05OTnMycnh+fPnOX/+fLZr167QQBRVUlhS6g/s3r2b7dq1U1ru9evXiz24tjDi4uJYuXLlMlvTH44GsrKyora2Njt27EgbGxulB5nyQiaTcd++fTQ0NGSlSpX4yy+/yNeXVLVBXREPHjygkZFRkYrt+PHjbNKkiUrbfffuHc3MzFR65uGGDRtoaWlZLp9TUaSlpfHEiROcO3cuv/nmG5qbm9Pc3JzffPMN586dyxMnTpQoYcWff/7JsLAwmpubs1WrVjx06FCxa4xbzj+gS1gU7SccyKfwPn3ZTzhAl7Aobjn/QEVPXf6okSQEvjgXL17EgAEDIBaLsWrVKlSpUkUlcpOTk9GyZUtYWVmhVq1aOHv2LOLi4uDo6AhfX1/4+vrCx8cHlpaWKmmvMHbs2IEtW7bg4MGDCu+Hh4fj4cOHWLp0qVJypVIpjIyMkJSUBGNjY6X7FRgYiCpVqmDGjBlK15XJZNi3bx9mzZqFnJwcTJw4EdevX0dkZCQGDBiAefPm4eDBg6hdu7bSslVJWloa2rZtiypVqiAgIADTp0+HTCZDUFAQZs+ejZ07d6Jx48Yqb3fFihVYu3YtWrZsifnz5ysss3v3bmzZsgV79uxRads//PADrl27hq1bt6pM5rZt2xAaGoqoqCjUqlVLZXKVgSSSkpIQGxuLmJgYxMbG4vLly3B0dISXlxfq168PLy8vuLq6Ql1dvUD97Oxs/PLLL1i6dCkyMjIQEhKCPn36wMDAIF+5n2MeYvahRGTlyUrcN10tdUzyd0Wgl31ZH7P8+cKK919DaX3g796946hRo2hubs7NmzerxNJ6+fIld+/ezf79+1NHR4daWlps0KABx48fz4MHD6p8HackdOvWrcj8nyEhIVy8eHGpZPv6+vLYsWOlqvvo0SOamJgo5eaTSCTctm0bq1evzjp16nDPnj35Zs/Tp0+ns7Mz165dq7LMJ6UlNTWV9evX56BBg+R9lMlkXL16NbW0tOjo6MioqKhySc3Vpk0bOjs788iRI4WWWb9+PYOCglTedlpaGsViscrdkxERETQzM+OFCxdUKrcs5OTkMC4ujsuWLWPPnj3p5OREQ0NDNm/enJMmTeK+ffsKuJplMhlPnz4t32oycuRI+Trm5aRUuoRF5bPqKvdfSV1HT6rrGlJNW5e6Vb1oNeSnAtafS1gUrzz++7s9BYuvjFx5/AYrTt1F9O1XAIAcyV8zJB1NdRBAE2cxghs74Ssbo3x1o6KiMGTIEDRq1AiLFy+Gqamp0u2TxKNHj3D69Gn56+nTp6hZsyauX7+Orl27YsmSJdDR0SnTc5aF3NxcmJub48aNG4Valu3bt0ffvn3RoUMHpeWPHj0aZmZmGD9+fKn6N3HiRDx9+hQbN24sslxeXh5+/vlnzJ07F2ZmZpg8eTJatWoFNTW1AmXnzp2Ln376CdOnT8eIESOwceNGfP3116XqX2lJSUlBy5Yt4evri/DwcHk/X79+DR8fHwwYMADW1taYOnUqjI2NMWPGDDRr1kzh8yhLZmYmzMzMoKamhpcvX0JXV1dhufDwcCQlJSE8PLzMbX7KzJkzcffuXWzatEmlcvfv349+/fohMjISDRo0UKlsVZGcnIwLFy7IrcLY2FiYmJjkswpr1aqFChUqICkpCStXrsT69evh7e0NjSZDcDlZhg+aQZadjqfrgiFNfw1dR0+oaWgh8/Y5aJnaonK/5VBT+8uyVFMDWrmZY1Vg3S/05CVD80t34J/Me3fAH8iWSKFo+pD9PyV49OYL/H47GZP8XRDoZY+XL19i5MiRiI2Nxdq1a+Hn51fiNmUyGW7evJlP0eXl5cndlkOGDAFJtG3bFvPnz8eAAQNU9bil5vfff0e1atWKdKc+ePAA9vb2pZLv6emJiIiIUvYOGD9+PKpVq4aEhAR4eHgUuJ+dnY0NGzZg3rx5qFq1KtauXYtGjRoVqSAmTJgAbW1thIWFYc2aNejXrx/Cw8PRvXv3UvdTGV6+fIkWLVqgTZs2+OGHH+R9zc7OxjfffAN/f3+MGjUKABAQEIAdO3ZgyJAhsLS0xMyZM+Hr61um9k+ePAl7e3tYWFgUqvQA4M2bNzAyMir0flkICQmBk5MT7t69CycnJ5XJbdeuHbZs2YIOHTqUm5u4rJiamsLf3x/+/v4A3o8bt2/flivCjRs34vbt23B3d5crwujoaByJPoelD3IADS25rOwniZCmv4ZGJXOYdZ4KAHj6UwjyXj5A5q3zqOjSUF6WBE7eeoWU9ByI9Ct83odWgoJOYIES8ZcPXLHS+xgSyMqTYvahRAwN3w53d3dYW1vj2rVrxSq93NxcnD9/HvPnz0f79u0hFovRoUMHXLhwAS1atMCJEyfw7Nkz7Ny5E8OHD0dWVhbatGmDJUuW/C2UHgDs3bsX33zzTaH3SeLhw4elVnx169bFxYsXS9k7wNDQEFOnTkVoaCg+doBkZGQgPDwcjo6OOHToEHbs2IFjx46hcePGJbKKQkNDMXLkSIwaNQobNmzA2LFj8eOPP5a6nyXl6dOnaNy4MTp27JhP6UmlUgQGBsLa2jrfmpuGhgZ69uyJmzdvIigoCH369EHLli0RExNT6j4cPHgQlSpVKvb3XZ6Kz8jICEOHDsXcuXNVLrtVq1b45Zdf0LlzZxw7dkzl8lWNuro6XFxcEBQUhB9//BEJCQl4+fIl5s+fDysrK0RERMDPzw8LIn4v8NtW03yvBGVZach78xyStGRI018DAPJePijQlhqAiEtPyv2ZyoLg6iwFVx6/Qbe1McjKk8qvJR9YjOyHlyHNSoO6th60LZxg3LgPtC0c81eW5mJBK0t0bl5foez09HScP39ebs1dvHgRTk5O8PHxkVt1lStXVlj3yJEjCAwMxJYtW9C6dWuVPW9ZIAk7OztERUWhevXqCsskJyejatWqSE1NLXUbJiYmuHXrFszMzEolQyKRoGbNmpg/fz4aNWqEFStWYMmSJWjUqBEmTpyo0BIsKatWrcKcOXOwYcMGDBw4EP3798f48eNV4lL8lMePH6NZs2b47rvvMHHiRPl1khgxYgSuXbuGw4cPo0KFwmfjeXl52LBhA2bNmgV3d3fMmDEDderUKXEfSMLe3h4aGhqIiIgoMrinT58+aNasGfr06VNi+crw+vVrVK1aFRcvXoSDg4PK5Z85cwYBAQHYsGHDZ3dlqwqSkMlkkEgkCN4ci+P33+W/L5PixbYJyHlys0Bd/a9aQdQmpMD1jrWsEN71ywQAlQTB1VkKVpy6i2yJNN81yduXqGDrDvUKesh+dBXZDy7hZcpjWAdvyFdOTVMbx59poPP/3r969QpnzpyRK7rExER4eHjA19cX48aNQ4MGDVCpUqVi+xQREYHg4GDs2bMHPj4+qnrUMnP58mVoaWnBzc2t0DIPHz4s06CkpqaGOnXq4OLFi3LXjrJoamoiLCwMQUFBUFNTQ+vWrXHy5Mki+11SBg8eDG1tbfTp0wdbt27F0KFDkZqainnz5qlU+T148ADNmjVDSEgIRo8ene/ewoULcfLkSZw+fbpIpQcAWlpaGDhwIPr06YN169ahffv28PT0xIwZM1CzZs1i+3Hjxg1IpVJkZmYWG/2oKotPJpNBKpXKXxKJRP53YGAgwsLCMHv27ELLFHatJGX69euH7t27o2vXrqhRo4ZKZX+OMjKZDGpqatDU1IRJx0nQqZJ/fU5NXQPm3ecg44/TyEt+DE1DMbIfX0fmzWio6ykem9Ky88r8nZYngsWnJMnpOWg470S+IJZPyXl+F883jgTU1GE7ZjfUNPLPLzTVCJ+Uw4j9/TiePXsGb29vuTXn6empdCDK+vXrERYWhkOHDn2xMOvCmD59Ot6+fYvFixcXWmbnzp3Yvn07du/eXep2JkyYAB0dHUydOlXpus+fP8fixYuxfv166OjoYODAgaWSUxybN2/G+PHj8euvvyI0NBTu7u5YvXo1NDQ08s26SzOI3b9/H8HBwejZsyc6dOiQr9zx48exceNGzJ49G8bGxkrLzsrKwoULF3D27FnY2NjAy8urSDlXr17F06dPoa2tDU9PzyLbunbtGiwtLaGnp1emQZwkNDQ0oKGhAU1NTfnfGhoaUFNTQ0pKCiwsLFChQgWFZUp6rbAyr1+/RlRUFBo1agQ3N7dSyymPMiWpp6amhidPniBkWzwSUgvaQ5TmQe1/637SzLd4unYIZFlpMO8+Bzp2BSdDgsX3LyMivnDfdVr8fuQlP0b2oysAAMN6HQooPeD9WovUzhPbtvVDzZo1oaGhUer+LFq0CMuWLcOpU6dQrVq1UstRBYpm3bt378aMGTPw/PnzQgexc+fOQU9PD3FxcaWe0aampuLs2bMQiUQlHjDfvHmDuLg43Lp1C05OTvDz80NmZqZ8D5iGhobKZ92ZmZlo1KgRKlSogIsXL+Knn34C8N7d9GHWrewgJpFIcP/+fVhZWeHcuXOIjY2Vl3nz5g2uX78Ob29vHDx4sNSDqLe3N+rVq4eLFy9i586dqFatGlq3bo3KlSsXqBcbGwuRSIRGjRrBz8+vSNnfffcdJk+eDFdX1zIN9Ir2rH3M999/j/T0dKxYsaLcfv/Xrl1Dq1at0KNHD/Tu3bvc2lEFubm5SEhIwPnz53H+/HmcO3cOmZmZMG7QBXTxg5pmfq/Aix1h0NAzhFqFisi+Hw9ZVhp0HT0VKj0dTXW4VDYocP3vhKD4lOSP52mFWnuZf5xFzuPrAAANA1NUsFLsJqO6JtI1KyExMRHXrl0rdsBUdC0vLw+nT5/GnTt30K5dO4SHh39xVwqAfIORmpoaMjMz0bdvX2hqahY6iD1//hy6urr4448/Sj3rzcrKwr1793Dz5k2FbWloaEBLSws6Ojp4+/YtTp8+jevXr8PLywvdunWDsbGxXNabN2+Qk5ODnj17lsvMfP/+/Rg/fjy2b9+OpUuXIisrC7t374a+vr7Sv8erV6+iVatWWL9+PXr16pXv3pUrV+Dn54ejR4+qNPLw3bt3+L//+z8sWbIEbdu2RVhYmDzhQmpqKkJCQqCjo4MJEybAzs6uSFm5ubnw9fUttlxZCQ0NhYuLCyZOnAgrK6tyacPd3R0nTpyAn58fcnJy/jbBZcB7r8YHBXf+/Hn5pve6detCV1cXenp6ePbsGbLO7IKZW8H4AG0zB2QknoYs+x009E1g6PUtjHx6KGyLAL6tbV3OT1Q2BFenkvTdFIcTf7ws9D4luci6fwmv9swB1NRgNXANNI3MC5QzyngM11fRpRpE1dXVcfDgQSQlJWHw4MGoVKnSF3WTFDbrXr58OeLi4ordR+Xv74/g4GC0bdu2dF8K3ltMFhYWiI+Ph7W14v90iYmJmDt3Lg4dOoTg4GCMGDECIpGoQLk///wTNWvWRHx8fKkjTYsjMjISgwYNwu7du7F27VrcuXMHBw4cUCr7THx8PL7++mv83//9H7p06ZLvXlJSEho2bIhFixYVuKcq3rx5g/DwcKxYsQIBAQGYPHkyzp8/j+XLl+PFixe4fft2sTIqVaqEpKSkEq1jl5XQ0FBIJBKlswMpy927d9GiRQuMGTMGw4YNK9e2FJGXl4erV6/ms+bevn0LLy8veHt7o06dOnj58iXWrl2LCxcuAADq1KmDQYMGIT4+HpEpZtC0r4338ZnKIezj+5diqFPwI5Pl5UBNQxNq6hpQ09SGbpU6UNPWAXMyIXn7QqHi8/Wqi2U9Bivdfl5eHoKCgqClpYUbN258lgGjtOzbtw+DBg0qtlxZ9vB9QE1NDXXr1kVcXFwBxXf58mXMmTMH0dHRGDFiBJYtW1bk52ZlZYVhw4Zh0qRJKk159TEdOnSAlpYWOnbsiF27dmHXrl1o0qQJjhw5AgsLi2Lrx8TE4JtvvsHq1asLbPp//fo1WrdujdDQ0HJTesD77QIfNugvXLgQHh4eMDU1RZUqVUoUBCOVSpGRkVEgXVZ5MWbMGFSvXh3jx48vNDJaFTg5OeHUqVNo3rw5cnJyEBoaWm5tAe8D5GJiYuTWXHx8PGxtbdGgQQM0b94ckydPhr29PX777TesWrUKs2bNAknY2tpi/vz5CAwMxPbt2/H999+jc+fO2DqpNwb/+ke+qPWSoqOpgeAmqtszWV4IFp+SrIq+h/Dfbudzd2Y/uork/QtRwaY61HX0kfP4BvKSk6CuVwlWA9dAXadiPhmyvBy8Ob0V6reOw9XVFS1atECPHj3g6upaZNtZWVno0qULSGLnzp1Fbgz+0rx9+xY2NjZ4+vRpkS48ktDT08OrV69K5er7mGnTpiE3Nxdz5swBAMTGxmLWrFmIj4/HmDFjMGjQIFSsWLEYKe9JT0+Hs7Mz9uzZg3r16pWpX0Vx5MgR9OrVCzt37kR0dDS2bNmCY8eOFTkROH36NDp16oSNGzcWiGLNzs5Gy5Yt4enpiUWLFpVbvxXx7NkzODo6Ijc3F23atMHatWuLVOKpqamoUqVKqbexlIYRI0ZAU1Pzs3w2T548kW/VmDRpkkpkSqVSXL9+PZ819/LlS9SvXx/e3t5o0KAB6tevDyMjI0gkEpw4cQIbN27E3r17oaamJo8uDg4ORtWqVREVFYXRo0fDxsYGixcvRo0aNQAAC/bEYNnZP6GuVfJAu39Srk5hA7uSfFunoBtNw0AETWNLZD+4jPQrxyDLToeeiw/Mu88uoPQAQFdXF79vnIexY8dCW1sbK1euhJubG7S1teHo6IiePXti165dyMnJkddJS0tDmzZtYGhoiD179vytlR7wPh2br69vscrsxYsX0NfXL7PSAyC3+KKjo+Hn54cuXbqgTZs2uH//PkaPHl1ipQcA+vr6mDFjRoFN7aqmVatW2L59O7799ls0bNgQISEh8PX1xc2bBfdMAcDx48fRqVMnbNu2rYDSk0ql6NWrFywtLbFgwYJy63NhJCUlwd7eHjo6OrCysoKbmxvGjRuH5ORkheXLc/N6YYwbNw4bNmzAy5eFL1eoCmtra0RHR2Pbtm0ICwsr1e8oNTUVUVFRCAsLQ4sWLWBiYoKuXbsiNjYWDRs2xJ49e/D69WscPXoU06dPh5+fH65evYpBgwZBJBKha9eu2LNnD/z9/bF//34kJycjPDwceXl5aNOmDUaOHIkFCxbgyJEjcqWXlpaGOX3bQP/2UehoqaO4HTdqaoCulsY/RukBgsVXKgZuuYhjiS+KzdiiEJkMem/uYnVg3XxpoXJycnDgwAHs3r0bMTExSEpKgkQigYmJCapVq4akpCQ0bdoUmzdvLjaC7e9A9+7d0bRpUwwcye+RqwAAIABJREFUOLDIcufPn8eIESPkaw2lhSR27NiB3r17w97eHhMnTkTPnj2hra1daplSqRS1a9fG1KlTERAQUKb+FUd0dDS+/fZb/Pzzz3j58iXGjh2LAwcOoG7dv9ZKoqKi0KdPH0RERKBRo0b56pPEyJEjcfXq1WI3qJcXU6ZMwa1bt/D48WOcO3cOT548wezZs/Hrr79iyJAhCA0NzbeGmZCQgL59+yIhIeGz9nPo0KHQ19fHvHnzPkt7r169gp+fH1q2bFnk3k2ZTIbExMR81tyTJ0/g6emJBg0awNvbG15eXgXWpUniwoUL2L59O7Zu3QqSyMrKwldffYXBgwcjICBAPrFMSUnB9OnTsX37dkyaNAnBwcH5/o/IZDJ4eHggKSkJjx49wsM0GVaeuouTt14BJHKkfw16GpBCU1MLTZ3FCG7ihJrWn3cSUybKOwv2vxFF2ctL+nKcsI8zV2yig4MDmzdvzjNnzihsQyaT8caNGwwJCaGOjg61tbUJgBUqVKCzszP79u3LQ4cOqezMPlWSk5NDIyMj/vnnn8WW3bZtGzt37lzqtqRSKSMjI1m3bl1Wr16dJiYmKs3If/ToUTo5OZXqJGxlOXPmDMViMQ8cOMDIyEiKxWKePHmSJBkZGUkzMzOeP39eYd0FCxawRo0aX+TkjQ/Url2b3bt355QpU/Jdf/DgAfv160eRSMRp06bxzZs3JMkTJ06o/Cy+kvDo0SMaGxvz1atXn63NlJQU1qlThyEhIfKTMN68ecMjR45w2rRpbNWqFStVqkRHR0cGBgZyxYoVTEhIKPQAaJlMxoSEBH7//fe0sbGhqakpRSIR7ezsOGvWLD569Chf+dzcXC5dupRisZhDhw4t9NmDgoKopaVV4AT75HfZnLP7Am27hrHvxgvsuewInb8ZKpzA/l9j87kHdBgXqZTSqzbpIKu26cuePXvy9evXXLduHe3t7enn58dz584VaOP27du0s7PjggULSL4/amXjxo0MCAigjY0NNTQ0qKamRrFYTD8/P4aHh5dI2ZQ3x44dY7169UpUdvbs2Rw3bpzSbUgkEm7fvp01atRg7dq1uXv3bkqlUnbs2JHbt29XWl5RtG7dmuHh4SqVWRgxMTE0MzNjZGQkT5w4QbFYzHHjxtHc3JwXL15UWGfr1q20sbEplxPUS8rTp09pZGREDw8Pnj59WmGZO3fusHfv3hSLxZwzZw63bt3KDh06fOaevmfgwIGcOHHiZ2tPJpMxLi6Ojo6OdHFxYfXq1VmxYkX6+vry+++/Z2RkZKGn1H/MzZs3OWXKFFatWpWmpqa0t7enoaEhBw4cyHPnzik8XurQoUN0cXGhn59fkQfprlq1ihoaGtywYYPC+4mJiaxatSrJ94dmK3uc198JQfGVkvXr17Oqf186hx0q9oRi23H76PB9JLecf8CMjAz27duX1apV4+XLl5mTk8M1a9bQzs6OrVq1YkxMDEny8uXLrFy5MteuXVtoH6RSKWNiYjhq1Ch6eHiwYsWKBEAdHR3WqFGDQ4cO5alTpz67VThs2DDOnj27RGUHDBjw/+ydd1RTWfu2Y6H39EDovTdpSpMq0hRQFAUUOx0VFYdBQVGxodiwK/bC2HHE3sfGKNaxoOJYsDGCdHLu7w9/yQdCIAnBed935lrLtWaSc3b2ITnn2fsp94M1a9YIPHZjYyM2b94MAwMD9O3bF0VFRa1u9uzsbEyZMkXoOXfEvXv3QKPR8PnzZ7GOy4+bN2+CwWBg3759yMzMRM+ePfn+PU+fPg06nY67d+/+kLnxY8OGDQgODoaiomKnv7eHDx9i2LBhUFBQQJ8+fVBTU/ODZvn/ef78OchkMj59+tQt41dXV+P06dOYO3cu/P39QSaToampidDQUOjq6sLf3x91dXUCjfX06VNkZ2fDwsICVCoVpqamkJeXx4ABA7B7926+49y/fx8DBgyAgYEBjh492mHPxd9++w0SEhKIiYnhe8zt27dhbm7O+//hw4dj3bp1Al3Dfxr/Gj4RePDgAahUKu7du4c7ryoxYdsNGKQXwTC9qJXBM0wvgkF6ESziVoCib4OCggLeGAUFBaBSqcjPzwdBEGhoaEB+fj7U1dXh6OgIMpmMvXv3Cj23iooKrFq1CgMHDgSTyUSPHj3Qs2dPsFgsBAQEYO3atQKtLEWFIAioq6t3uLJsiZeXF44fP97pcXV1dVizZg20tLTg6emJs2fPtnsjFxcXw9XVVeh5d8b48eMxefJksY/Lj9u3b0NJSQkqKio4dOgQ2Gw2VqxY0eqYO3fugEaj4dy5cz9sXvwICQlBbGwsAgICBD4nNTUVenp6YLFYWL58ucCGQFzExMRg1qxZXR6HIAg8ffoU27Ztw6RJk2BlZQVZWVk4OTlhypQp2L9/fytPzNevX+Hp6Ylhw4bxXSSUl5dj8eLFsLOzA4VCQZ8+fcBkMmFqaopFixbhzZs3fOfz8eNHJCQkgEqlIjc3t1M3/Zs3b6CgoAALCws0NzfzPe7atWvo06cP7/+3bduG4ODgDsf+T+VfwyckdXV1sLCwaNNN/GN1PfLPP0X89htgDJmN5N0lyD//rQN7RUUFKBQKlJSUcP/+fd45Dx8+hLm5OcLDw/HlyxcAwJEjRyAvLw8qlYqAgAC+7i1BaWhowKlTpzBhwgSYmJhASkoKPXr0gJycHGxsbDBlyhT89ttvfGMJwlJSUgJdXV2BO3rr6el1GJOrqalBbm4uVFVV4e/v365LuCWfPn2CgoJChzewKLx79w4UCoXXpbq7Wb16NRgMBuh0OrZu3YqysjLo6uoiKysLBEHg5cuXYLPZ2LNnzw+ZT0c0NDRASUkJERERWL58ucDnZWRkYPbs2SgpKUFgYCDYbDZWr179Q+KpwLedFIVC4cUcBaWmpgbnz5/HggULEBwcDDqdDjU1NYSFhWHJkiW4evUq6us7jn3V1tbCz88PISEhvOt99+4dVqxYAWdnZ6ioqMDZ2RmmpqagUqlITEzErVu3OryvBI3jtaSurg76+vpQVlbu9PgLFy6gX79+vP//8OEDFBUVO73W/0T+NXxCEhcXhyFDhnT4A1RSUmrjQtm9ezdYLBYMDQ3x9etX3uu1tbWYMGEC9PT0sGDBAtBoNFy6dAn19fVYuXIl1NTUEBQUhJKSErHMnyAIlJWVYeHChejfvz8oFApvV6iuro7Q0FAUFBSIHPifPXs2UlJSBDq2ubkZUlJS7a70v3z5gvnz54PBYCA0NFSo69fV1W21wBAXc+fORVhYmNjH/Z6lS5dCS0sLZWVlePDgAdTU1LBx40a8efMG5ubmmDRpEoyNjbF06dJun4sgnDp1CnZ2dtDQ0MCDBw8EPi8xMRHLli3j/f+1a9cwYMAAaGpqYv369T/ERR8VFYU5c+bwfZ8gCLx48QK7du1CQkIC+vTpA1lZWdjb2yMpKQm7d+9GeXm5SJ9dX18PPz8/mJubw93dHUpKSvDw8ICrqysUFRUxePBgHDx4UKCFwLFjx2BoaNhpHO/7axs0aBCkpKRw/fr1To8/efIkPDw8Wr3m5OSE4uJigT7vP4l/DZ8QHDhwAFpaWp1mzhkbG7eJuRAEgcGDB8Pc3ByRkZFtDOe4cePQs2dPTJ8+vdV7dXV1yMvLg6qqKgYNGoTbt2+L74L+j+rqahw4cACRkZHQ09ND79690aNHDygoKMDBwQE//fQTbt26JdAuytraWmDX26tXr8BisVq99unTJ8yaNQtUKhUjRowQ+CZuSXh4OLZu3Sr0eZ1RU1MDNpvNNxNXHMyfPx96enqtsvL++OMPqKurIz8/n+eWMjU1FdsuvaukpKQgISEBampqAu/0gW9GZ8uWLW1ev3TpEjw9PaGrq4utW7d263U+evQIVCoVVVVVAL7db5cvX8bixYsRGhoKFosFBoOBQYMGYeHChbh48SJqa2u79JlfvnxBQUEBBg4cCAUFBTAYDNBoNDCZTPTp0wcrVqwQeOEpTBzve7KzsyElJYVVq1YJdPzRo0fh5+fX6rU5c+YgKSlJ4M/8T+Ffwycg5eXloNPpnbraAMDT0xMnTpxo8/rbt29Bo9Ggq6vbKmll0aJF0NTURHFxMaytrREaGtrGuNbW1mLZsmVgsVgICQnBnTt3un5RfOBwOCgtLUVGRgacnJygqKiInj17olevXtDW1kZERAT27dvXZlf78uVLUCgUgR9UFy5cgJOTE4Bvbp5p06aBTCZj7NixePLkicjzX7x4MeLj40U+vyO2bt0KBwcHoR4wgkAQBGbNmgUjI6N2M3OfPn0KDQ0NWFlZITQ0FF5eXggJCfmPcDMZGBhg2rRpGDVqlFDnBQUF4eDBg3zfP3fuHFxcXGBoaIidO3eCw+F0dapt+PPPP+Hs7Ix+/frB0dERsrKysLGxQVxcHLZv346ysjKxfNdfv37Fnj17MHjwYCgoKMDX1xfR0dGwtrYGi8WCiYkJ7OzsUF1dLdB4Hz9+RHx8vMBxvO8pKiqCtLQ0hg0bJvA5hYWFbbJwS0pKoKenJ9Rn/yfwr+ETgKamJri4uGDevHkCHR8VFYVNmza1+962bdugr68PCoWCkpISpKWlwcjIiJcWXFdXh7i4OGhra7frfqipqcGSJUvAZDIRFhb2w7L53r9/j+3btyMsLIxXStGzZ08oKyvDxcUFc+fOxYwZMxAZGSnwmAUFBRg0aBASExOhoqKC+Pj4NvVHonDu3Dk4Ojp2eZz24HA4sLGxwe7du8U2JkEQmDFjBszNzfkmHhEEgVGjRkFaWho5OTmor69HWFgYvLy8BH5YdgdPnjwBk8lEUFAQduzYIdS5rq6unXoHCIJAcXExHBwcYGpqiv3794tsABsaGnDt2jUsW7YMQ4cOhbq6OigUCtzc3CAnJ4eioqJWYYiuUl9fj4MHD2LYsGFQUlKCt7c3EhIS4O/vDyUlJQwfPhy//vormpub0dzcjDFjxqBv374dxhxFieN9z6NHjyAnJwcjIyOhEop27tyJ8PDwVq8RBAEWi4XHjx8LPY+/k38NnwDMmjULnp6eAt9wM2bMwNy5c9t9jyAIBAYGYtCgQVBUVISVlRXev3/f5rh9+/aBRqMhNze33RXn169fsWjRIjAYDAwdOrRbYlod0dDQgCtXrmDq1KmwsbGBjIwMSCQSevbsCX19fYwePRqHDh3iWwLw7Nkz2NraQlpaGlOnTu0wS01YqqqqICsr220xorNnz0JLS0ssWYgEQSA5ORk2Njb4+PEj3+O4Bep3796Fnp4e5s+fz3tYOjg4dFtafmcsX74co0aNgpKSEt69eyfUuRYWFgK77gmCwLFjx2BrawsrKyscOnSo053Y27dv8csvvyA1NRXOzs6Qk5ODhYUFJkyYgC1btuDx48e8MYYOHcqrl+0KjY2NOH78OKKjo6GiogI3NzekpaVh7NixoNFocHZ2xvr169s1bhwOB7GxsbCzs2v3vuHG8Xx8fEQKAQBAZWUl2Gw2lJSUhF5kbt68GVFRUW1eHzNmzA+rcxUX/xq+Tjh37hyYTKZQD+YVK1Zg0qRJfN9/8eIFpKSkQKVSMWjQIL438LNnz9CnTx8EBQXxfbB9/foVOTk5oNPpGDZsmFDJBeKksrIS8vLyWLZsGfz9/cFgMNCzZ0/07NkTZDIZnp6eWLJkCQ4fPozIyEhQKBRYWlp2W4KGsbExfv/9924ZG/jmplu4cGGXxuBwOJg0aRIcHBw6jBvv3LmzVYH669evYWhoiMzMTBAEgSlTpsDMzEysiwdB8fHxwbx582BhYSH0uRoaGnjx4oVQ5xAEgQMHDsDCwgJ2dnY4fvw4CIJAU1MTbt26hZUrVyIiIgLa2tpQVlbGgAEDkJWVhZMnT/Iyp9ujtLQUTCZTpJrC5uZmnDlzBuPHjweVSoWjoyOysrKQnp4OMzMzaGlpISMjQ6CMYIIgkJKSAisrK95uritxvJY0NTXB1dUVsrKyOHXqlNDn5+fnY9y4cW1e/+WXX+Dt7S3SnP4u/jV8HfDx40ew2WwUFRUJdV5hYSHf+pba2lr4+/vD0tISZmZmsLKyQl5eHt+xGhoakJycDE1NzQ7ji9XV1Zg/fz5oNBoiIiLEKtslCLt27cLAgQPbzKm4uBixsbHQ0dFBz549ebtCAwMDqKqqIjs7W+h0ckGIiorq1uLaR48egUKhiJz92tzcjJiYGDg7O3f4QD59+jRoNFobl/bbt29hYmKC9PR0cDgcZGdnQ0dHB8+ePRNpPqJQXV0NeXl5zJw5UyTRAEVFRZG/+4qKCkybNg0UCgWKioqQlpaGsbExxowZgw0bNuDBgwdCu0RDQkIE3rlwOBxcvnwZCQkJYDKZsLa2xpw5c5CXlwc/Pz8oKytj9OjROHfunNDzIAiCFwKJiYkBjUbDsmXLuuzBSExMhKKiosAhm+9Zvnx5u7HzqqoqyMvL/60ud2H51/DxgeuSFKVo+erVq7Czs2vz+pcvX+Dq6oqIiAg0NDTAz88PycnJoNFouHbtWodjcrUbFy5c2OGNVFVVhezsbNBoNIwcOfKH+d6HDRvWprYR+JaiHhgYCBaLhUWLFuH69etYvHgxPDw8eDvCXr16gUajYcCAAVi5cqVID63vycvLw/jx47s0RmfExcWJlETT1NSEESNGwMPDo8OYErdAnavX+T3v37+HhYUFLxN41apVUFNT+2Fx34MHD8LDwwPOzs749ddfhTq3ubkZvXr1Euh7bm5uxp07d5Cfn4+oqCjo6+tDUVER3t7eSE9PR2pqKnR1deHm5oYLFy6Iejn4/fffwWKx+GZtEgSBmzdvIjU1FRoaGjA2Nsbs2bOxc+dOjB8/HmQyGV5eXti2bVuXYoWNjY1YtmwZZGVloaysLJbvc/PmzVBUVERAQIDIO8aFCxfyXeB4enriwIEDXZniD+Vfw8eHvLw82NrailRMW15eDlVV1VavvX//HjY2NoiNjeXd7OXl5aBSqVi6dCk0NTU7jdO8ePECjo6OGDhwYKc7jS9fvmDOnDmgUqmIiorqUpZkZ3BFqVu62s6fPw9vb29oaGhg5cqVbR4mTU1NkJSUxJ9//onCwkJER0dDV1cXvXv3hoSEBKSkpGBhYYHk5GQUFxd3uCtqj6tXr8La2los18eP9+/fg0KhCLW7bmxsRFhYGAYMGNBhWjy3QL2zJJqPHz/C2toaKSkpIAgCO3bsAJ1O50nfdSfjxo1DdnY25OXlhXYRfv78GcrKynzfKyoqws8//wwvLy8oKirCwMAA0dHRWLt2LUpLS9uU1jQ1NWHz5s3Q1taGl5cXXzHvzggKCmqjkHPv3j2kp6dDT08Purq6mDlzJk6cOIGsrCzo6+vD0NAQ8+bNE7mejws3jtkyjrdgwQLo6uoK7RJuyZUrV6CgoABtbW2h76OWzJkzh6++6dKlS9t1g/6n8q/ha4fff/8dVCpVZGPR2NgICQkJ3s1ZXl4OIyMj/PTTT21WW+vXr4eNjQ0SExMREBDQ6Qq4sbERU6dOhbq6Ol8x4Jb89ddfyMzMBIVCwejRo7vFFcYVpSYIAidOnICLiwt0dXWxceNGvguH58+fQ11dvc3r3My72bNnw8nJCXJycpCQkECvXr3AZDIRHByMdevW4dGjRx2uXGtrayEjI9PtMlg5OTkCyzbV19cjKCgIgYGBHZYhfP78GSYmJgLHPz9//gw7OzvExcWBw+HgyJEjoNFoIsVxBIUgCKipqWH16tVtipoFoaysDFpaWuBwOLh//z7Wr1+PmJgYGBsbQ15eHv3798fMmTNx5MgRodzJjY2NWLt2LdTV1TFw4EDcuHFDqHnduHEDbDYb9+7dw5w5c2Bqago2m40pU6bg/Pnz2LJlCzw8PEAmkzFp0iT89ttvYil3uH//Pnx9fduN4y1btgyampoiqQa9evUKVCoVioqKXU6AS09PR2ZmZrvvPXr0SOg6zr+Tfw3fd1RXV8PQ0BDbt2/v0jgMBgOvX7/GH3/8AU1NTSxevLjd4wiCgLe3N7KysuDo6ChwwsTRo0fBYDAwb948gdxFlZWVyMjIAIVCwZgxY/D8+XNhLqdD4uLiMHLkSNjZ2cHExAQ7duzotJbvzJkzcHFx6XRsrnJGQUEBhgwZAjabjd69e0NKSgrS0tKwsbHBjBkzcPr06TYxBisrq27f+dTV1UFLS6vTtPza2loMGDAAYWFhHXoR6urq4OLiIrD6DZe//voLTk5OGD9+PDgcDs6dOwcajYZffvlFqHEE5fbt29DV1UV8fDzmz58v8HlfvnxBcXExJk6cCAUFBSgrK0NHRwcjRozAqlWrUFJSIpaCda7ykaqqKoKDgwXKHn3x4gUWLlwIRUVFKCgoID4+HhcuXMCpU6cQHR0NZWVl+Pv7Y+/evWJbUHHr8TqL461ZswZsNlso70JNTQ0sLS2hoqIiku7v96SmpmLBggXtvkcQBHR1dbs1oUyc/Gv4vmPUqFGIjo7u8jjW1tbYvn07WCwWNmzY0OGxL168AIVCwcmTJ8FgMATayQHfVnP9+vWDj4+PwMLTnz9/Rnp6OigUCsaNG9clFwq3NZCEhASMjY1RWFgocGxu48aN7aZGCwJX+T41NRVWVlY8I9irVy+w2WwMGTIEmzdvxtChQ9u4rbqDXbt2wcbGhu+1f/36FR4eHoiIiOjwoc7hcBAWFoahQ4eKFOOsqqqCi4sLRo0ahebmZty8eRNMJrNddZSukp2djYSEBBgZGfHVkyUIAn/88Qc2b96M8ePHw9zcnNeKJzw8HGZmZkKXQAhLbW0tcnNzeXWv3+963rx5g+XLl8PJyYl3T6xYsQIsFgtpaWnQ1NSEhYUFlixZIta5cuN43Hq8jkpZuGzatAmqqqoClTIQBIGhQ4eCxWKJrVtJYmJih8k/iYmJAndl+bv51/C1YMeOHTAwMBBLdpKTkxOUlJSwb98+gY5fs2YN7O3tcfjwYbDZ7HZr+9qjqakJaWlpUFNT45sE0R6fPn3CzJkzQSaTMWHCBKFqehobG7FlyxYYGBjAwsICTCZT6Af1zz//3KZhqahwOBzcu3cPq1atgr+/P2g0GiQkJNC7d2/06tULDg4OmDVrFs6ePSvWAmUuBEHAwcGhVfcNLl++fIGzszNGjx7doeQbQRBISkqCm5tbl9RYvn79iv79+2PkyJFoamrCw4cPoa6u3koTUxz07dsX27ZtA4VC4X331dXVOHPmDLKzs+Hv7w8KhQINDQ2Eh4dj+fLluH79Om+3+8svv/zQXnwty35CQ0ORmZkJd3d3KCsrIyoqCseOHUNFRQXWrl2Lvn37QlJSEl5eXmLfwbQXxxOGHTt2gMlkdjqv7OxssFgsuLm5iU3ybcKECVi9ejXf93/99Vf07dtXLJ/V3fxr+P6Pp0+fgkqlikUM+vjx45CWlhYq44/D4aB///7IyclBWloafHx8hOow8Ouvv4LJZCIzM1Oo8z58+IAZM2bwYhYdNZasr69Hfn4+tLS04OHhgTNnzmDWrFlCu+UAYOTIkXwbXoqD9+/fIzc3F2QyGcbGxpCQkICsrCx69+4NTU1NjBw5EgUFBXj69KlY4hKXLl2Curp6qySPyspKODg4YOLEiZ0uDBYvXgxTU1OxdFCvqamBt7c3r+3NixcvoK+vj1mzZonlWj9+/AhFRUVkZ2fD3t4esbGxsLa25rXimTx5Mvbt24c///yT7xibNm0SWuKsK1RWVmLz5s3w9PSElJQUpKSk0L9/f5SWlqKoqAjh4eFQUlJCaGgoDh8+jHPnzkFbW1usIgjcOJ6hoSGOHTsm8nexb98+0Ol0vsLSBw8eBJlMhqqqqlhbkI0aNYqvIhXwzU2voKAg0O717+Zfw4dvCRV9+vQRqqUKP/bs2QM6nY6YmBikp6cLde6zZ89AoVBw9+5duLq6IisrS6jzX79+DTc3N3h4eODt27dCnfv+/XueVmZcXFyrh1ZNTQ2WLVsGNTU1DBw4EJcvX+a9J4wodUucnZ2F2qGKQmNjI2RlZVFdXY2Ghgb89ttvyMnJQf/+/Xm1X9LS0pCXl4ezszPmzp2L8+fPi9wYNTQ0lOfq+fjxI2xsbJCUlNTpA45boN7VrMCW1NXVYeDAgQgNDUVDQwPevXsHKysrJCQkiORGra2txYULF5CTkwMbGxtISkpCRkYGNjY2WLJkCa5cuSLUTnXp0qVITk4Weh7CUF1djZ07d/Ia5A4aNAi7du1CdXU1Ll++DCcnJ/To0QM0Gg1z5sxpk1Xt4eEhlsWZoHE8YTh8+DBoNFqrexEA7t69CxUVFaioqIg9vj1s2LBOZekCAwOFlq77O/jX8AGYOnUqAgMDu7waXrduHVRVVXHnzh2sX78eo0ePFnqMFStWwMnJCeXl5WCxWEJn5jU1NSEjIwMsFgsnT54U+vMrKiowdepUngs0LS0NDAYDISEhuHXrVqtjhRWlbomamlqX4ouC4uDg0G5tF0EQeP78ObZv346oqChoaWlBQkIC8vLy6N27N3R1dRETE4MdO3YILFTM7e929+5dmJubt+m00R7cDuqlpaUiXyM/uFmkQUFBqK+vR2VlJfr164fIyMgOvzNuv79du3YhMTERdnZ2kJWVhZ2dHRITE9GvXz9kZ2eDTqeLnCTF7cUnbmpra1FYWIihQ4dCUVERAwYMwJYtW/DXX3/h/fv3WL58OWxsbKCmpoYZM2bg6tWrSEtLA5lMRmxsbKsF37lz56Cnpyeyq7BlHC8+Pl7sO6Hjx4+DSqXyFp4fP36ElpYW1NTUkJ+fL9bPAoDBgwdj//79HR6Tn5+PiIgIsX+2uPnHG76ioiKw2WyRFTi4LFy4EFpaWryC8WPHjsHX11focTgcDlxdXbF06VKcOnUKLBZLJCkq7rnp6elC37ifPn3ClClTICMjA0lJSYwcObLdHeSKFStESlCpr6+HpKTkD2mrExcXhyVLlgjWiBGXAAAgAElEQVR0bFVVFU6dOoWff/4ZDg4OkJGRgZycHKSlpaGgoAAPDw8sWLCgw9Y048aNg7KyskBuxc4K1MVBQ0MDQkND4efnh7q6OtTU1GDAgAEICgriZSbW19fjypUrWLJkCUJDQ6Gqqgo6nY5BgwYhJycHFy5c4F1vc3MzKBQKTpw40SVV/u978XX1Go8ePYrIyEgoKyujf//+WLt2LT58+ICGhgb88ssvCA4OhpKSEkaMGIHi4uI24YD3799j6tSpUFFRQXJyMu/37urqim3btgk1n5ZxPF9f327V0T19+jSoVCqKiorg7u4OIyMjjBo1qlvKCgYOHIgjR450eEx5eTkoFIrYG0GLm3+04Xvz5g2YTGaXHjxcZX1jY+NW8bHff/8d5ubmIo355MkTUCgUPH78GJmZmSIHqN++fQtPT0+4urp2GG/hUlFRgenTp4NMJmPMmDF48uQJ3r59i+TkZJDJZKSkpLTKbPPy8up0Bdgejx8/hra2ttDnicKWLVswfPhwkc7lJs3k5+cjNDQUTCYTkpKSUFRUhISEBAwNDTFx4kTs2rULL168wIsXL6CtrQ05OblOkxYELVAXB42NjQgPD4e3tzdqampQVlYGJycnqKurw97eHrKysrC2tkZsbCy2b9+OZ8+e8X1wXrp0CRYWFli0aFGHerSdwa8Xn6A0NTXh1KlTGDt2LCgUCvr27Yu8vDy8efMGBEHgxo0bvLY9rq6u2Lhxo0DF22/evOF1C0lNTUVhYSEMDQ0FfpDfu3dPLHE8Ybh48SJkZGTAZrNhY2PT5X6B/PD09BSo6ay5uXkbF+x/Gv9Yw8fhcODl5dWlzEIOh4OJEyfC1ta2zY7x/fv3IJPJIo+9dOlSuLi4oLGxEd7e3nwVEzqjubkZWVlZYDKZOH78eLvH/Pnnn0hKSoKKigri4uLadUFyHwhkMhlTpkzBkydPRNbnKy4uFqnoWRTu3bsn1n5h79+/x6FDh5CSkgILCwtISkpCSUkJUlJS6NmzJwwNDREUFARHR0e+tV7cAnVBd6JdobGxEdevX8eSJUugqakJKSkpkMlk+Pv7w87ODoaGhkK5nNPS0njJV12pEeysF197cDgcXLx4EXFxcaDT6bC1tcWiRYt4GcmvX79GTk4OTExMoKOjg9mzZ4ss2PDq1StMmjQJKioqYLPZrfpntseHDx8QFxcHKpUqtjieoOTn54PBYKBHjx7d4uLk4uzsjPPnz3d63IwZM0R+Xv0o/rGGb/78+XBxcemS/3748OFwc3NrdyXJ4XAgKSkpcqFrc3MzbxVbUVEhklh2S86dO8eLa3CvuaysDBMmTICKigqmTJkikEv1zz//RHx8POTk5KCjoyNw2UVL1q5di5iYGKHPE4Xm5mbIy8vzbY/UVRoaGrB3714oKyvDxMQESkpKkJGR4WmQmpiYICEhAXv27EF5eTnq6urg6uoqUiasILx79w4HDhzAtGnTeK14zM3NMX78eGzatAkhISFwcXFBVVUVCILA9OnTYWJiIpBHAPjWSuj06dOQl5fvUgaqIL34gG8elevXr2Py5Mlgs9kwMzPD3LlzeapKtbW12LlzJ3x9faGsrIwxY8bgwoULYttpPX/+HL6+vujVqxcyMjLaiGp3dxyvM86dOwcKhQI6nY6VK1eCwWB0mxfBzs5OoISZixcvwsrKqlvmIC7+kYbv6tWroNPpImfR1dTUYODAgQgMDOzQraCpqdkliTBuB4Bnz57hwoULYDAYXcr8q6iogK+vL6ytrREWFgYKhYKffvpJpPhmUFAQ3NzcQCaTMX36dKHGSEtLw5w5c4T+TFFxcXERKdFHEO7fvw9VVVWeSAE3aSYpKQlkMhl6enqQlJQEmUyGtLQ0JCUlwWKxsHjxYly9erVLNXtNTU0oKSnBypUrMWLECOjo6PBa8WRmZrarccrhcDB+/Hg4OTnxHuILFiyAtrZ2pxJ9r1694sX3HBwcRJ430HEvPoIgcOfOHaSlpUFHRwd6enpIT0/niTUTBIGLFy9i7NixUFFRgY+PD3bs2CFyNm5nEAQBCwsLuLm5gUajYd68eaiqqsLRo0d/SByPH2VlZaDT6TAxMeH1/ywtLQWLxcLWrVvF/nkWFhYC1TU2NTWBTCYLvJj6O/jHGb7KykpoaWmJrCT+119/wcXFBSNGjOjUneHk5CSwCgs/Fi5cCHd3d3A4HOTk5MDR0VEk4WzgWzLF0KFDIScnBzk5OezatUukcVqKUr98+RITJkwAmUzGzJkzBWqIOmzYMKETBrrC5MmTRW7F0hG3b98Gk8ls91oIgoCzszM2btyIqqoqnDx5Eo6OjrwdoZKSElRUVCApKQlLS0ukpKR0Wvv24cMHHDlyBDNnzoS7uzvk5eVhbGyMmJgYbNiwAffv3xeoVIEgCMTHx7dqeJqfn8/LSObH2rVrERERgRkzZghdqvM97fXie/ToEWbPng1jY2NoaGggNTUVt27d4u3enj9/jszMTOjq6sLY2BgLFiz4YQ/Xo0ePwsLCAvfv34efnx8kJSVBo9FQWFj4t+hTVldXw9zcHC4uLggKCmr1vT948ABqampib8tlaGgocL/PYcOGdeoe/jv5Rxk+giAwZMgQxMbGinQ+t8MCVwy4M0JDQ7vsdmhuboa9vT1Wr14NDoeDgIAAoVslXbt2DUFBQWAymVi0aBGqq6tx8eJFqKurY8qUKUIbUq4odUtevHiBcePGgUKhID09vUPXoqOjIy5duiTUZ3aFnTt3IiQkRKxj3rhxAwwGo0MNxGvXrkFVVRXV1dWtCtQ5HA7u3r3LMyRsNhvS0tKg0WiQkZEBjUbDoEGDMG3aNEyfPh2RkZEwMDCAgoICvLy88PPPP6OoqKhL7ltuw1Nra2uee2737t2g0+m4cuUKPlTXY825p0jaXYLRW64jaXcJHEenY+3WnbC1tRUo1tMR3F58ZWVlmD9/PqysrMBisZCYmIgrV67w7q+qqips3rwZbm5uoFAoiIuLw/Xr13+4seHu+vz8/ECj0TB9+nQMHjwYLBYLy5Yt63Yx9JZwOBwMHjwYrq6u0NfXb7en4ZMnT6ChoSFWyT4tLS2BPVgFBQU/VJlHWP5Rhm/dunWwsLAQ6UdaXl4OQ0NDpKenC3zTJSYmiqXD+P3790GhUPDixQt8+vQJmpqaAiUWXLhwAT4+PlBXV2+3NdCHDx/g7+8PBwcHoeqx4uPj+WrylZWVYcyYMaBQKMjIyGg3DsRgMH6oG+TJkyftdoIQlStXroBOp+PQoUOdHjt8+HCEhoZ2WqD++PFjZGRkwMnJCQoKCryGvVJSUujduzeMjY2RkpKCwsJCsXVa58b4zM3NeQofq/ccg9qwTOjOPAqD9CJozjjK+6cxpRD6Px0Da0gGbpQJH9vl8vLlS/Ts2RP29vagUqmYMGECzp49y8uc5HA4OHXqFCIjI6GkpITAwEAUFhZ2yS3cFbhxPEVFRdBotFZu/ZKSEgQGBoLNZmP16tU/ZI4ZGRmwtLQElUrtsFff8+fPoa2tzVcgX1hYLJbA9+379++hqKj4t31nnfGPMXz3798HlUoVeKveEm6HBWGz8BYsWICpU6cK/XntMW/ePHh5eYEgCPz222+g0Wjtrr4IgkBxcTFcXV2hq6uLDRs2dLij43A4WLRoEWg0mkDuX4IgoK6u3mm6/rNnzzB69GhQKBTMnj2btyqtra2FlJRUlxvNCgNBEFBWVhaLyPD58+dBo9H4Zsh+z86dO9GjR49WQgQcDgcPHjzAhg0bMGbMGJiYmEBeXh7u7u5IS0vDkSNH8Pr1a1y9ehVLlixBcHAwyGQyFBQUwGQyISMjAyaTiSFDhiAvLw83btwQOYuQIAikp6fDxMQEK0+Uwujn49BqYeza/Tf9MIx+Po5tV58L/DkVFRVYtWoVXF1doaSkBElJSfz666+t5v3o0SPMnDkT6urqsLKyQm5urlglt4SFIIhWcbx79+7B0tKy3Vq269evY8CAAdDU1MT69eu7Latz7969YLPZ0NTUFChUUV5eDn19fV4MsCuQyWShYvmOjo7dFlvvKv8Iw1dbWwszM7NOuyS0B7cr88aNG4U+d9u2bSLXkH1PU1MTbG1teX57rgIFd/dKEAQOHToEe3t7GBsbY/v27UJlrF69ehWamppISkrqcJVWUlICXV1dgXe9T548QXR0NKhUKrKysnD9+nXo6+sLPC9x4eXlhaNHj3ZpjJMnTwrV5660tBQ0Gg0hISHw9fVFVlYWBgwYABUVFWhra2PEiBFYuXIlbt261el31VJpZtKkSTA2NoaUlBQYDAaoVCqkpKTg4OCAadOm4cCBA0Ib+eE/r4Lm1F86Nnjf/TP6uahD4/f582ds3LgR3t7eUFRUxPDhw3Ho0CE8fPgQWlpavGPWrFkDR0dHMBgMTJ48ucM444/i3r178PHxgZGRUats6v3798POzo7v7//y5cvw9PSErq4utm7dKlaRhpKSElAoFDg7Owsl9/bmzRsYGxsL5a1qDzk5OVRVVQl8fFZWVrfL0onKP8LwTZo0CeHh4UJ/6RcvXgSNRhOpSBv4pqrg5uYm0rntUVpaCiqVivLychAEgdDQUEycOBF79uyBhYUFrKyssH//fpF3U58/f0ZwcDBsbW35+vJFFaV+/PgxIiMjoaioCD09PaFuIHEwY8aMLklkHTt2DDQarV35s5ZwW/EsWbIEcnJyUFdXh6ysLCQkJBAdHY0DBw4IraPKD67STGZmJjw9PSEnJwcKhQJVVVXIyMhATU0Nw4cPx4oVKzo0rrfLK2H08/FWRk3e0gcSFHX0kJBGT2kFSOvYgjVmVTvG7zjuvKpsNaft27cjICAACgoKCAkJwZ49e1p1xbh+/Tp0dHQwZMgQKCoqYsiQITh69OgPUfLpDG49Ho1Gw/Lly9vs3DgcDkxNTTvd8Z87dw4uLi4wNDTEzp07u6xk8u7dO2hoaCAsLAyurq5C7ygrKipgYWGB1NRUkY1f7969hcoHuHXr1t+yyBWE/3nDV1hYCG1t7XYDwB1RVFQEKpWKEydOiPzZDx8+FGvxNADerqGhoQFr1qyBhIQE9PX123RtFhWCIHh1Se21VBJVlJpLRkYG9PT0eGnh4mgBJQiFhYXw9/cX6dyDBw+CTqfj6tWrbd77+vUrzp49i+zsbAQEBIBKpUJNTQ2KiooIDg7GtWvX0NDQgJUrV/Jc1d1Fy6SZyMhIaGhoQFZWFmw2GzQaDdLS0nB2dsaMGTNw6NAhXg3muIIb0EprbdBIJBIkVQ0hb+mDXkoMkEgk9FKgQOO7XaFW2lGM2fIb9u3bh9DQUCgqKsLf3x8FBQVtSinu3LmDyZMnQ0VFBQoKClizZk231VcKS0NDA3Jzc0GlUjutx9u1axccHR07/S65YQcHBweYmppi3759Ii1K6+vr0bdvXwwbNgxqamoiL5w+fvwIW1tbJCQkCP075HA46NGjh1DnEQQBFovFk3H8T+J/2vC9ePECNBpNaJXyltltXaGqqgqysrJifdhVV1fzHmT9+/dHfn4+KBSKUJ2ZBeH69evQ1tZGbGwsz53aFVFqLqmpqZg/fz4ePnyI4cOHg06nIycnp1v65LXk5cuXYDAYQn8Xe/bsAYPBwM2bN0EQBJ49e4bt27cjLi6O14rH0dGRV47w9OlTuLq6tnHxNDY28mSsfiQVFRU4ePAgpk2bBgcHB0hLS4PJZEJdXR0yMjLQ0DeB1vRDbXZyjJGLeP+tNnEjSCQSSCQSmKOWtTlWY+ovcB8QiPXr17cpZ6moqEBubi6srKygrq6OmTNnYsWKFQgODv6hfwd+cON4BgYGAtfjNTc3w9DQUOD4FVe709bWFpaWljh06JDAv0OCIBATEwNvb2/Q6fQuS4FVVlbC0dER48ePF8oIc2PzwhITEyP2XpDi4H/W8DU1NaFfv37IyckR6ryWHRbEgby8vNC7zfaoqanB8uXLwWaz0a9fPygpKfEyrNauXQszMzOxF/BWVlYiNDQUVlZWePz4scii1C0JCwtrFZS/f/8+wsPDwWAwsGjRom4zgARBCC1asHHjRlAoFCQnJ2PQoEFgMBhgsVgIDQ3F4sWLcfny5VYZwhwOB0OGDOHbQf3w4cMwNjb+W1169fX1vKSZkJAQMPtHQmNqYYexPNXxa78Zvh49oRZf0OZ9g5+OIf/801afsX//fgQGBkJJSQmRkZE4deoU72+yadMmREdH/01/gf8PvzieIGzbtg3Ozs5C74AOHDgACwsL9OnTB0VFRZ2ev3z5cpiamsLMzAwrV64Uao78qKqqgouLC6KjowV2wVZWVkJRUVHozyosLISPj4/Q53U3/7OGLz09HT4+PkKtanJycgRSsBAGQ0PDLqk6VFVVYcGCBWAwGBg8eDBu3rwJ4JvLMCAgAARBgCAIjBgxQqQ2SJ1BEARWrVoFKpUKMzMzFBYWdmk8W1vbdnfgd+/exZAhQ8BkMrFkyZJuUeEYOHAg3zIQbiue3bt3IykpCVpaWujRowfMzMyQkJDAE6Lm96DidlB3dXXlWy5DEATc3d2xZs0asV1TV0naXdKh0VOfvA9SakYgkUhQdAjhe1zy7hJcu3YNsbGxoFAocHd3x+bNm9uN5S5duhRJSUl/w9V+48OHD4iNjeUbxxOEpqYm6OnpiSRwz+FwsHfvXhgbG8PJyQmnTp1q93dVXFwMBoOB4OBgREZGitVz9PXrV3h6evKaFXfGu3fvQKfThf6cL1++iKzp2538Txq+M2fOgMViCewLb9lhQdz1Zf379xcppffz58+YPXs2qFQqhg8f3qZep6GhAebm5jzVkOrqahgbG3fYIbkrnD9/Hj169MCoUaO6pP5OoVA6zDi8c+cOQkJCwGKxkJubK1al+VmzZiEtLQ1A651PWFgY1NTUQKfTERwcjODgYNDpdKF2/dwC9c5iVrdu3QKDwRCoU8CPYPSW63yNGTtxByRZ+iCRSJC39IXG9CN8j9UelQNdXV1kZWV1WhOakZGBWbNm/ZDra0nLOF5CQkKXdTU3b96M/v37i3x+c3MzduzYAX19fbi6urYSBXj8+DHodDoSExNhaWnZLQvB2tpa+Pn5ISQkpNOklZcvX4pcC+vh4SG0IHl305P0P8aHDx9IkZGRpC1btpCYTGanx3M4HFJsbCzp1KlTpAsXLpDU1NTEOh9VVVXS69evBT7+/fv3pLS0NJKenh6pvLycdOXKFdLOnTtJZmZmrY6TlJQkbd68mTR58mTS27dvSfLy8qT9+/eTpk2bRrp7965Yr4FEIpHevHlD8vb2JtXX15McHBxIjx49EnqM6upqUm1tLYlOp/M9xsLCglRYWEgqKioinT9/nqSnp0fKy8sj1dfXd2X6pDdv3pAaGhpIO3fuJPXt25dEJpNJkyZNIj179owUHBxMOn/+POndu3ckNzc3UmlpKem3334jWVhYCDT27t27ScuWLSMdP36cpKKi0uGxNjY2JF9fX1JOTk6XrkcUAJBevXpFKi4uJuXl5ZEmTZpEunbxbLvHNn95T3q3fRqp8e0TkqJjGInil0Dq0aMH37GbaqpI/fr1IzEYDNLXr19JBEHwPfavv/4iKSsrd/l6BAUA6dixYyRzc3PSiRMnSBcuXCDl5eWRKBRKl8YdMWIE6cWLF6SLFy+KdH6vXr1IERERpAcPHpBGjx5NGjVqFMnb25t08uRJUlBQECkqKoq0e/duUmFhIUlWVrZLc20PGRkZ0oEDB0gcDocUEhLS4T1WX19PkpKSEulz/P39SUVFRaJOs3v4uy2vOCEIAv7+/pg2bZpAxzc0NGDYsGFwd3fvthX4tGnTBNKJ/PPPP5GcnAwVFRXExsYK3ComLS0NgwYN4rlBCgoKYGhoKPZygWHDhmHt2rUgCALr1q0DlUpFQUGBUGOUlpbC2NhYqHNKSkoQFBQENTU1rFixQiDVHW4rnuXLl2PYsGHQ1NQEmUyGp6cnZGRkcPr06XZdL/PmzYOenp5QccAzZ86ARqMJ1UH91atXIJPJXRIc74iGhgbcv38fhYWFmDt3LkaOHAlbW1vIy8uDyWSif//+mDRpEvLy8jBlw3Ho/9R2B9dLnvwtk1ORBoU+Qbx/zKglbY7VSj0AhvsIKCkpQV1dHRQKBXJycvDw8EBGRgaOHz/eSsEnKioKmzdv7pZr/56uxPEEYf369fD29hbLWI2NjcjPz4e0tDTU1NRAo9F+SDJUY2MjhgwZAh8fH747y9LSUpiamoo0/sOHD8Fms/8WTVN+/E8ZvtzcXNjb2wvks66pqYGfn1+rTtTdwbJlyxAfH8/3/efPn2PixIlQUVHB5MmT8fr1a6HGr6+vh4mJSauEkbFjx2LYsGFi+6G1FKXmcufOHRgaGmL06NECJ6QcOnQIAwcOFGkON2/eREBAANhsNlatWtWqyL5l5qKLiwvk5ORgZmaG8ePHY/PmzXj06BHvb8Fms/H06dNWYxMEgYyMDBgbGwslB8YtUD9z5ozQ15Oeno6RI0cKfV5Lvnz5gmvXrmHLli2YMWMGgoODYWhoCCkpKejr6yMwMBDTpk3Dpk2bcPXq1VbGhyAIXLp0CUOjxrQpUeCWM7T3jzIwua2rM/UAfrt9H2VlZdi1axeSkpJga2sLSUlJMBgMqKqqQkpKCjo6Ohg9ejQsLS2Rl5fXreo9LeN4eXl53aak0tDQAA0NjXZLXUSB+xvW0dGBgoICgoOD+XaxECdNTU0YOXIk3N3d210U3rhxAzY2NiKNTRAEdHR0fsh1CMr/jOG7desWqFSqQCKq3A4LI0eO7PaGkfv27cPgwYPbvP7HH39g1KhRvK4GovS143Lt2jUwGAyevFNtbS0sLCzElkTRnig18C2uGBkZCRMTk04lzIBvGWqiCoRzuXLlCvr16wdlZWXY29tDW1sbysrK8PX1xezZs1FcXNxhFu3gwYNbLRLa06sUhPLycrDZbJE7XFRVVYHJZOLGjRsdHkcQBF6/fo1Tp05h5cqViIuLg6enJ1RVVXmd0yMiIpCVlYV9+/bh7t27HSrvVFZWYsWKFTA1NYWBgQGWLFmC6A2XO5cp4/NPK+0ofOfsB4vFatOypq6uDlevXsWyZcsQHh7OK6yXlJSEvLw85OTk0L9/f8yePRsnTpwQS/azuON4grBmzRqRF3Qt2bZtG3R0dDBhwgT4+/vj69evyM3NBZPJRFhYmED3WFdobm7GmDFj0Ldv3zbfxaVLl+Dk5CTy2AkJCd3SIUVU/icMX1VVFfT19QV6CFVUVMDa2hrx8fE/RC/y8uXLrXqXlZaWIjw8HDQaDVlZWWIr4E1NTUVYWBjv///44w9QqVTcunWry2N3JEpNEAQ2bdoEKpWKjRs3drjLTE5OxqJFi4T67I8fP+Lo0aOYOXMm+vfvDwUFBRgZGSEwMBCmpqZgMplYs2aNwIoS8+bNw5QpU3hzT0pKgo2NjVAPyM+fP8PU1LTL4r9r166Fq6srCIJAU1MTHj16hIMHD2L+/PmIjo6Gvb09TxjZ1dUV48ePR25uLo4fP44XL14I/PslCALXrl1DTEwMlJWVER4ejrNnz/IygtOXrofGlI5LGvj9M/y5CHdeVWLfvn2g0WidtuF6+/YtNDU1MXr0aPTr1w/S0tIgk8mg0+mQlJSEjo4OYmJisHHjRjx8+FCoazxy5AgMDAwwYMAAkTR5RaW+vh5sNrvTRUxHXLt2DTQaDTk535KEWj4Xvn79ioULF4JOpyMiIgJ//PGHOKbdLhwOB7Gxsa1aVgHfVKjc3d1FHvf48ePo16+fOKYoFv4nDF9UVJRAHb1fvnwJAwMD/Pzzzz/M3/z8+XOw2Wxcv34dwcHBYDKZWLhwodhjcLW1tTAwMGiltrJnzx7o6Oh0qVO2oKLU9+7dg4mJCUaOHMk3dXnQoEEdyr81NzejtLQUa9euxahRo3iteDw9PZGeno6ioqI2BdJXrlyBj48PtLS0BBIH5gp4czgcTJw4EQ4ODkL9fbgd1JOTk0X6DVVXV+PmzZvYtm0b0tLSoKCgAHV1dUhLS0NHRwcDBw7ElClTsH79ely6dKlLO5aqqirk5+fDysoKOjo6WLBgQatd7ZcvX+Dn5wc6nQ5V16HQTBVOq1N72gFYD0nk/f1+/fVXUKnUTuW8NDQ0eJmfzc3NuHPnDtauXYvo6Ghoa2vzet0pKirydoVZWVk4efJku7H4e/fuwdvbu9vieIKwYsUKBAUFiXTu69evoaamhuXLl4NKpfJ1CVZVVWHu3LmgUqmIjo7uUpPrjuC2rLKysuKJUhcVFcHX11fkMevq6qCgoCBQv84fwX+94SsoKICRkVGncaY//vgDGhoaYmkTJAynT59Gjx49wGazsWLFCrGm53/P5cuXwWQyWymox8fHY/DgwSIbemFEqWtqahATEwNDQ8N2SwEsLS15dYjAN7fbr7/+ioyMDHh7e0NJSQn6+vqIiorCmjVrcPv2bYELbC9dugQvLy9oa2tj06ZNfIvEP3/+DAUFBURHR8PFxUWoBQi3QH3IkCEd7kQIgsC7d+9w9uxZrFmzBomJibz2UDIyMrCwsEB4eDhmzZqFGTNmQENDQ6zJVSUlJZgwYQKUlZUREhKCEydOtJrvp0+fkJaWBikpKcjKyiIpKQl3797FtqvPv3VnSOvcvWn083FsvVyGhIQEmJub88qALl++DDqd3mEfSkVFxQ4XG5WVlSguLkZWVhY8PT0hLy8PBQUFUKlUSEhI8HaFeXl5iIiI6PY4niDU1dVBVVUVJSUlQp1XW1sLOzs7pKenQ09PT6AGzZWVlZg1axYoFArGjh0rcCKcMBAEgbS0NJiamuLdu3c4cOCAyIadS0BAAHbu3CmmGXaN/2rD9/jxY1Cp1E7rrUpKSsBisbqtxu17CILAyZMn4ebmBh0dHcjLy3dbBt/3pKSktOoIUV9fjz59+rAGIAAAACAASURBVCA3N1ek8WbNmiV049uCggJQqVReFijwzWjIy8sjLy8PY8eO5bXicXNzQ1paGg4fPtylOCeXCxcuwMPDA7q6utiyZUsbA9jU1AR5eXk4ODgIrRKTnJzcqkC9ubkZT548wZEjR7Bw4ULExMTAyckJKioqIJPJ6NevH8aMGYPFixfj6NGjePbsWbuG3MfHB3l5eaJfNL65wzZu3Ah7e3uoq6tjzpw5rRKlGhsbcfjwYYSEhEBGRgZSUlJITU1t8/e586oSE7bdgG7aEWhNO9jarZleBIP0IkzYdoMnTE0QBBYsWABNTU2ee/HOnTtQVVVttwN4c3MzevbsKVSYgSAIPH78GNu2bcPEiRNhaGiIXr16oUePHpCQkICsrCzc3d0xZ84cvhm7P4Lc3FyhGh5zhSfCw8MREBDQYRJce3AXMGQyGbGxsWKvQSYIApmZmTA0NMTq1asxZMiQLo23Zs0ajBgxQkyz6xr/tYavvr4eNjY2ncr4XLhwATQarcuKI4JAEAQOHz4MBwcHGBkZYdu2bWhqaoKlpaVYYm2CUFNTAz09vVa99crKyviKLHeGqKLUN2/ehLa2NszMzODt7Q1lZWX06NEDERERvG4B3blCP3fuHNzd3aGvr4+CggI0NTWhoaEBoaGhYDKZWL9+vcBj1dbWYvLkyWCz2UhNTcWQIUNgbm4OGRkZaGpqwtfXF8nJycjPz8f58+dRUVEh1A67tLQUdDpdJJf03bt3ER8fDzKZjMDAQBw9erSVcf3999+RnJwMOp0OBwcH2Nvbw8jICA8fPuxw3IjR4xE1vwB9ElbAY/Ze0IKmYvWZx/hY3X7izJYtW8BgMHj6to8fP4aWllYbycDPnz9DSUlJ6OsEWsfxfHx8sG3bNixatAj+/v6gUCiQkZGBiooKb1c4evRoFBQU4MmTJz8ktFFTUwMmkylwaUtOTg5sbW2RkZGBvn37CtX5oCXv37/H1KlToaKigqSkJLF1/+CyYMEC0On0LndU52r9drVThTj4rzV8KSkprerX2oPbSqa4uLhb59Lc3Iy9e/fC0tISlpaWbVTY/fz82m1e2V2cP38eLBarlT/90KFD0NDQECpmJKgoNXdFvnXrVkyYMAEWFhaQlZWFk5MTLCwswGQysXr1alhYWIh8TaJy5swZuLi4QE9PD9bW1ggMDMSCBQvaXV1/+PABFy9exLp165CSkgI/Pz9oaWlBQkICvXv3xsCBA5Geno4dO3bg1q1bYtUVHTt2rMBNi2tra1FQUIB+/fpBVVUVGRkZrTwK7969w5IlS2BhYQENDQ2kp6fj6NGjMDIywujRoztVASEIAhoaGnjw4AEYDAbKysrAZrNRVlbW4XncjiaHDx8G8K021djYGNOnT+fdp2VlZdDU1BToOlsiSBzv1atX2L9/P1JSUmBpaQlJSUkoKipCVlaW512YO3cuzp49222asIsWLcLQoUM7Pe7o0aNQVVVFQUEBVFVVhS5jao83b94gMTERKioqSE1NFYsHhUt4eDjk5eXblAIJi5mZWZfF/8XBf6XhO3bsGNTV1TsMlHI7LIirvqY9mpqaeDFGBwcHHDlypF1DPGbMGOTn53fbPNojISEBkZGRrV6bOnUqBg4cKLCbiZ8oNbcVz7x58xAYGAgqlQp1dXUMHToUubm5vFY8XHbt2gUFBQWYm5v/LUWsNTU16NOnDygUCgwMDJCQkABDQ0MsXboU48aNg7OzM6hUKhQVFeHg4IBRo0YhJycHhw4d4rlthSlQF4U3b96ATCZ3aFwePnyIlJQUUCgU+Pr64sCBA7xFSV1dHfbu3Qt/f38oKysjOjoaZ86cAYfDwebNm0GlUrFlyxaB5vLs2TOwWCzcvn0burq6AAA3NzeBpPeuXbvWakf94cMH9OnTBxMmTEBzczNKSkpgaWkp0Dy454taj9fY2Ihbt25h1apVCA0NBYvF4hnD3r17Q0dHB6NGjcL27dvx7Nkzsfw2q6urQafTO9TnffDgAa/PJ51O77THo7C8evUKkyZN4pVKiSOhZMWKFXB1dQWbze5SJ5jp06fjp59+6vJ8usp/neF7/fo1mExmhz+WtWvXQlVVtdseVvX19Vi3bh10dHTg7u7OV2SWS0ZGBjIyMrplLvz4+vUrtLW1W+00Gxsb0bdvX8yfP1+gMby8vLB//36UlZVhx44diIuLg42NDWRlZeHg4ICUlBTs3bsXr1696nSsGTNmgEajISwsrEtZpoJSV1eH0tJSFBQUQEtLC5qamrC0tISUlBQkJCRAIpHg4+ODlStX4syZM3jz5k2b77ArBeqikJmZ2Wa3UF9fj127dsHd3R0MBgNpaWk840gQBK5evYqJEyeCTCbDw8MDW7du5cW4ampqMGrUKBgZGbXReu2I9evXIyIiAosXL8bEiRMBfGsvI+ji7fHjx9DW1kZmZiYIgsCXL1/g7u6O8PBwnDhxQqDmzA0NDVi6dCmoVCoSExPFlg348eNHFBUVYebMmbC3t4e0tDRkZWUhIyMDeXl5uLq6Yu7cuTh//rzI+pjz589HREREu+99+vQJenp6WLduHaysrLq1Zc/z588xZswYUCgUzJ49u0t1kosXL0ZKSgo2bdoEVVVVkWsKL1y4AGtra5HnIS7+qwxfc3MzPDw8kJmZyfeYBQsWiL3DApfa2lrk5eWBzWZjwIABndYsccnPz8fYsWPFPp/OOHPmDNTU1FoZmlevXoHBYPCN29XW1uLixYvIzMxE7969QaPRwGQyERISgkWLFrVpxSMo8fHxWLhwIeLi4qCtrY3r16+LfF0t+fz5M65cuYKNGzdi6tSpCAgIgK6uLqSkpGBgYAAKhQILCwts2bIF169fR1VVFc+VZ2ZmBlNTU+zdu7fNLri8vBzq6uoiF6iLwtevX6GmpoYrV67g6dOnmDZtGuh0Ojw8PLB3717eLrq8vBzZ2dkwNDSEvr4+5s6di5cvX7Ya68GDBzA1Ne2wvIQfERER2LBhA3x9fXnlJ9nZ2UhNTRV4jLdv38La2pq306utrUVgYCCsra0REBDA97yWcTw/P79ur8fjcDh48OABNm7ciBEjRkBTUxO9e/eGnJwcevfuDW1tbURFRWHHjh14/vy5QLvCqqoq0Gi0NjujpqYmeHl5ISUlBdHR0YiIiPghHpCnT58iKioKVCoV2dnZIiX/ZGdnY8aMGQCAHTt2gMlkthEsEISmpiaoqKiIxbXbFf6rDN/cuXPh5ubWbnCUq8BhYmIi9uymqqoq5OTkgMlkYtCgQUIXqh45cgR+fn5inZOgTJo0qU27ouPHj0NNTQ3v3r1DeXk59uzZg6SkJNjb20NWVha2trbw9fWFlZWVwDd7ZwQEBPAU2rnFzrm5uQKNTRAEysvLceLECSxfvhwTJ06Em5sbGAwG5OXl0adPH0RGRmLevHn45Zdf8PDhQ1RUVMDe3h6TJk1q17UbFRWFtWvXoqioCHZ2dv+Pu/cOi+r6vocXHQVC71JUkKKUUBRLsGDBLga7xi4ajUpU7IIaxYYNK6jBLmJvoIhiBQG7sRdiVxAQpQ4z6/eHL/MRacMwGL/vep77MNx72r1z5+yz99l7bTo4OHDfvn0UCoXMzMyUSYB6VVFYWMixY8dSU1OTurq6nDRpkjhY+fPnz9y2bRu9vLyoo6NDPz8/Xr58ucznt337durp6TE8PLzK351IJKKRkRHv3btHdXV1cRDznj17quSxSH6JE/Ty8mKPHj2Ym5vLwsJCNm3atFxHntu3b//n8XjkF3Pl2bNnOW/ePLZo0YLq6upUUVGhiooK1dXV2aJFC86fP58XLlwoNzxp/vz5pbYJxo8fzw4dOjA0NJSNGjWq8eTL3+Lr5M9Lly6tkkb7bUaNqKgoGhgYSLWA7dOnDzdt2lTlerLE/xnBd+nSJRoaGpZpVisqKqKfnx/d3d1lSlGUkZHBuXPnUk9Pj3379pXadHr16tUq7WvIEtnZ2bSwsGB0dLQ4Fc/y5ctpZ2dHFRUV6uvrs1u3bgwODi5h3ikmpZYVGjZsWCIw98mTJ3Rzc2P37t3FZqxvyZUHDBhQilz5999/5+rVqxkbG8sXL16UObGnp6fz559/rjDIPDQ0lKNGjSL5vyzcrq6udHBwYMOGDTlhwoTvth+ZmprKmTNn0tjYmC1atKCFhQV37NhBoVDIs2fPcsiQIdTS0mKnTp0YGRlZrsadm5vLkSNH0traWmpexLt379LCwoJnzpwpQVOXnJws1TtcUFDAfv36sXnz5vzw4QNDQkLo5OREZ2dncTB9Wloax4wZ80PE45UFkUjE1NRU7t69m8OGDaOVlRUVFRVZq1YtKioq0tLSkgMHDuTOnTv577//UiQSMSsri7q6umLLU3h4OBs0aMCTJ09SX1+fDx8+/M/u5/bt2+I9z5UrV0pkwZk6dWqpLZIjR45QX1+/ylnht27dWiaN4/fE/wnBl5GRQQsLCx4+fLjUtYKCAvbp04etW7eWGRvK+/fvxfExQ4cOrTZF0Js3b6inpyeTsVUFr1+/5v79++nr60tlZWXWrl2bzs7OHDNmDCMiIujh4VHm3mNZpNTVgUgkopqamniPoZhcOTw8nG5ubqxVqxbNzc3F5MrdunVjQEAA//7771LkypXh7du3dHBw4LRp0yoUXAkJCaX2GoqKitiiRQtqaWnRycmJhw4dqjHhJxAIxKTdurq6HD9+vNghYvv27dTW1qaFhQUdHBy4bNmySl3UHzx4QCcnJ/bp06dawfBr167l0KFDOX369BJOCBkZGVRXV5fqeQiFQv7555+0t7fnhAkTxHve1tbWnD17tsz38b4H8vPzeeXKFS5dulSshSspKYl5SJs3b85WrVqxS5cuPH36NPX19Xnx4kXWqVNH7PX6X+PrzCffEr9/i4kTJ5ZJ/hEdHU09Pb0qhTy9f/+eP/30U4X91TR+eMEnEon466+/cvz48aWuFWdY6N69u0wyLLx69Yr+/v7U1tbmmDFjKk2oKSmEQiGVlJRq9IsuLCxkcnIyV69ezX79+olT8XTq1Il//fUXO3XqxMGDB5eo8+bNG5qYmJQK9zh16lQJflFp8DW5cnBwMFVUVNimTZtS5Mrz589nQEAAdXR0GBwcXC3+1FevXtHW1pZBQUGVTtC5ubmsVatWiffG39+fnp6ezM3N5aFDh+jk5EQXFxceOXJEZgLw5cuXDAoKYp06dejh4cG///6bOTk5zMrKYnh4OFu0aEEDAwNaWlrS399fon4jIyOpp6fHdevWVXucv/76K7dv3043N7dSk5m2tnaViLy/xbJly6iurs4pU6bwyJEj1NPTo6qqKo8dO1atMf8oePfuHQ8fPswxY8bQ3t6eioqK4qwWBgYG4lg4SZzBvieSkpLo7e1NCwuLcmn/xowZw7Vr15ZZPy4ujnp6elUKG2vSpAlPnz4t9Zirix9e8BVzDX4rNLKystiiRQsOGjSo0jizyvDs2TOOGTOG2tra9Pf3l/keIfklHY4sqYWKU/FMnTqVnp6e4lQ8I0eO5JYtW0qk4iG/PC8zM7NSLulnzpyhkZFRiXuuiJT6W3xLrvzbb7+VIlfu0aMH69Spw5iYmHLJlVNTU9mkSRN27ty5BOWapPj3339pZWXFRYsWSVzH2dmZiYmJJMmQkJBSGdSFQiH3799PBwcHurm58dixY1JrPNHR0ezevbt4UVVMxxYTE8N+/fpRU1OTPXv25OHDh1lYWMi7d+9ST0+vQtN9fn4+f//9d9avX18mBAlCoZC6urq8ffs2NTQ0SgVUu7m5VTsGy8XFhQoKCrSwsOCJEye4ZcsWGhkZfTeCh++Jjx8/UkdHh5aWlmIOUgUFBSoqKlJdXZ1NmzblnDlzmJCQ8J9qP8W4dOkSvby8WK9evVKsR8OGDatwX+7ChQvU19eXeBEzd+5c+vv7V3vM0uKHFny3b9+mnp5eKe+od+/e0dnZmX/88Ue1NIQHDx5w6NCh1NHR4fTp06u1mq0MTZo0qbItvBgCgYDXr1/nunXrOHDgQNavX5+ampps3759lVK6REdH08LCopRJ+K+//mKLFi0oEAjKJaX+mlx55syZ7Nmzp3if8Gty5U2bNpUiV46MjJTIMaKwsJCTJ0+mmZmZxB6z5JegaEtLyyq7ho8cOZKhoaHcvXs369SpUy6tnFAoZFRUFBs1asTGjRszOjpaIgH45s0bLliwgJaWlnR1dWV4eDg/ffrEf/75hwEBATQxMaGbmxtDQ0PLFHBjxozhhAkTymz7yZMndHFxYc+ePWWSzockb9y4wQYNGnDv3r1lptnp06ePRFySZaF4H09ZWZkdO3Yswaa0f/9+6uvr89y5c9Ua/48EkUhEX19fceB3cdxxVlYWT506xYkTJ9LJyYmqqqpUUlISLwb69OnDHTt2/Kdej/Hx8fzll1/YoEED7tq1i0VFRRwwYECl331iYiINDAx44MCBSvtISUlhgwYNZDXkKuOHFXw5OTm0t7cvlam5OMPCnDlzpDbr3Lp1i3379qWenh7nzp0rs9RAFcHHx6dE5oSKUJyKZ+bMmWzTpo04Fc/QoUMZFhbGO3fuSC3whwwZwjFjxpQ4JxQK2aFDBwYEBDA2NpYmJiZct25dheTKe/bs4c2bNyUi3V60aJE4FZAkOHbsGA0MDLhw4cJK7/PBgwc0MzOTKvfgxo0b2aFDB4kzqAuFQkZGRtLe3p4eHh48efJkqXdQKBTy9OnT9PX1pZaWFkeMGMHk5GSmp6czNDSUbm5uNDExYUBAQIVBzuSXBZ6urm4pR4hiQbFq1SqZ7kEuX76co0eP5siRI8vkdp0xYwaDgoKq1Oa38XjNmjXj2bNnefXqVfF7Rn7J+ainp/f/G7Pn3Llz6eHhwatXr7JWrVrl8lyKRCI+fvyY4eHh7NGjB01NTSkvL08FBQUxp+zMmTOZmJgoNaWZNCjmG/bw8GDDhg3ZpEmTConHi3H16lUaGhpWWlYoFNLIyKhGws4kwQ8r+EaNGlUqzuX+/fs0NzeXmnA5OTmZPXr0oKGhIRcvXizz1EAVYezYsWVqJEKhkLdv32ZYWBiHDBlCGxsbamhosE2bNpw1axaPHz8u003/jIwMmpiYcPv27SXIld3d3SkvL09lZWWamJiIyZWPHz9eLrmypBg9ejRDQ0OrVOf58+ds3rw5O3ToUK4mfufOHZqYmEhNPh4ZGUkFBYUqB6gXFRVx9+7dtLW1ZbNmzRgbG8v3799z6dKltLKyoqOjI9euXcv379/z0KFD9PHxoaamJvv168eYmJgqPcvg4GCxB1xBQQEnTJhACwsLXrlypUpjlgRdunThnj17aGlpWWbA++bNm0uxAZWHYt5aa2trdurUSRyP5+joKI7/evLkCa2srDhr1ixxML6BgcEPw+AvLfbv3y9mOGnQoAFXr15NbW1tibdQcnNzefHiRU6bNo3u7u5UV1engoICFRQUaG5uTl9fX27btk1mzmcVQSQS8fjx49TU1GTdunUlcvi6desWjY2NuXXr1grLDR06lKtWrZLlcCXGDyn49u7dy/r165fwTrt69SqNjY1LaYCS4OLFi/T29madOnW4evVqqRkZqoOFCxcyICBAnIonMDCQ7du3p6amJq2srDho0CCuW7euSql4KkNOTg6vX7/OXbt2cc6cOezVqxcbNWpEZWVlKioqsm3btiXIlY8dO0YFBQWZB2136NBBqpW8QCDg9OnTaWpqWsrR4saNGzQyMuLOnTulGlNxgLqysrLUbP4CgYCzZs2ihoYGFRQU2L59e166dIkpKSkcP3489fX12aJFC4aHh0ttjszNzaW5uTn37NnDxo0bs1u3bjXi/SgQCKipqckrV67Q2Ni4zMktPj6ezZo1q7St4ng8Ozu7Urn5vs7FR37Rat3d3Tls2DAKBALeunWrhCb4fw03btygnp4er1y5wh49eoiZbyZNmlSmg56kePnyJbdv387evXvTwsKCCgoKlJeXp7q6Ot3d3Tl16lQmJibWWChI27ZtGRgYSEdHR7q5ufHEiRMVCsC7d+/S1NS0zAwdxdi3b1+1cvxVBz+c4Hv27Bn19fVLBIlLk2FBJBLx9OnTbNWqFevWrcuwsLDvvoEsFAp57949btmyhZ6entTU1KSamho9PT05bdo0Hj58WCb7imlpaTx//nwpcmVVVVU2bNiQvr6+YnLla9eu8fPnzxw4cGCpH+K///7L2rVr083NTaZmFRsbG6kpjsgvCU6NjIw4d+5cFhUVMTk5mYaGhhKbjr/F1wHqTZo0qfLeUkZGBleuXEk7Ozva2dlx+fLlXLx4MfX09Fi7dm0aGRlxzpw51Sb0LYa/vz8VFRW5dOnSGguvuHLlCh0cHLh+/fpytbpi1p/y8P79e3E8XmhoaJmTcFm5+D59+kRvb2927tyZnz9/5pMnT1ivXj0uWLDgP+F2lRbv37+npaUld+/ezYULF7JJkybiOefNmzfU1taWmZZWWFjIlJQUcWYHTU1NysvLU15enmZmZvTx8WFERITM/BY8PT159uxZCoVC7t27l3Z2dmzatCljY2PL/Y4ePXpEc3Pzcq09WVlZVFdX/+6B/OQPJviKmR2+ZswozrAgCUEu+T/KIw8PD9ra2opT0nwPZGdn8/Tp05w/fz47depEbW1tWlpasl+/fhw7dizd3NykXpEJhUI+ffqUJ06cYEhIiJhcWVdXl5qamvTw8BCTKx85coQPHz6s8L4/fPhAY2PjEpynxaTU3bt3r9bq9Ntxq6qqVvvlfvXqFVu2bEk3N7cSGQCqivz8fLZs2VIcoD527FiGhIRUWk8kEvHy5cscPHgwNTU12b9/f8bGxnL37t3s2LGjmBh6+vTpYg7X6jprFDv7mJub09bWVmrtVhIEBwdz/Pjx7NmzJ7dt21ZmmeLv8lsNuaCggCEhIZXG41WUi6+wsJC//fYbmzRpwrS0NL569YoNGzbk5MmT/08Iv4KCAnp6enLGjBk8deoUjY2NS4UtTJgwocq5LauCDx8+cN++fWIHOEVFRcrLy1NNTY2urq6cNGkSExISpJoPmzRpUsKjt6ioiDt37qS1tTU9PT3LfdefPXvGunXrlsuC1Lp16zLjs2saP5Tgmz59Or29vcU/jN27d9PQ0FCiDAvFnnfOzs50dHTk3r17azTvk0gk4qNHj7ht2zaOHj2aTk5OrF27Nps3b87Jkydz//79JVZ3//zzD21sbCptt5hcOTIyknPnzmXfvn3p7OzM2rVrs06dOmzbti3/+OMPrl27lmfOnOGbN2+knhgOHDhAKysrsem3bdu23L9/PzMyMli3bl2pNaqv8fr1a+rr61e7HfJLvFDt2rWpra0tVQyQUChk7969S2RQj4iIYN++fcutk5WVxbVr19LBwYFWVlZcsmQJjx8/zlGjRlFHR4dt27bl9u3bSwh2gUDAv//+m/Xq1WObNm2q5KFajOfPn7NZs2bs2LGjWKM3NzeXyJlIGrRv354HDhyoVCuxs7MTJ34ubx+vPFSWi08kEnHatGls0KABnz17xvT0dDZu3JjDhw//IXK4lQeRSMRRo0axa9eufPr0KQ0NDXn27NlS5V69elXtWMiqoJiHdMGCBWzZsiV1dHQoJydHeXl5mpqaslu3bgwPD5doPM7OzmWGnBS/63Xr1mXbtm3LDHd5/vy5mFP2WyxbtoxDRv/B9fGPOWHPNQ6NSOKEPde4Pv5xubkfZYEfRvCdPn2aJiYm4i9hw4YNNDU1rdTbTiAQcPv27bSzs2Pjxo1lGmz8NXJychgfH8/g4GB27dqV+vr6rFOnDnv16sUVK1YwMTGxQlNqsVpfjIyMDF66dKlMcmVbW1v6+Phw+vTp3LZtG5OTk2vMEadv3778888/mZmZSQ0NDfFqPjk5mXp6etX2urp06VIJ6itpERsbS319fcbFxTE2NpbGxsacPXt2lSbE4gD1r4PW79y5Qysrq1Jlk5OTOWLECGppabFXr17cuXMn586dS2tra9rY2HDhwoXlhj8Uo7CwkJs3b2bdunXZrl07iWPgTpw4QUNDw1IB/T4+PhJn1qgKCgoKqK6uztjYWDZq1KjCsl26dOGBAwd469Yttm3btsx9vPIgaS6+VatW0dTUlDdu3OCnT5/o5eVFX1/fHyLWrSysXbuWDRs25Lt37+jq6lohx+vYsWMZEBDwHUdXEp8+feLRo0c5bNgw2traUllZmXJyclRTU6OzszMnTJjAixcvltIK7ezsKtyuKCwsZFhYGM3NzdmxY8dSfMavX7+mnZ2d2JGJJG88z2S/tWdoPuUgG8w6QYtpx8SHzawTbDDrBEdtT+aN57LP5vJDCL53797RxMREbM4MDg5m3bp1K9wjKSgoYHh4OOvVqyfOFSYrgScSifjs2TPu3LmT48aNo6urqzgVz8SJExkZGVnppFfcTjG58ooVK6ioqMgWLVrQ0NCQGhoadHd3L0Wu/L15CtPS0sT7Z9/Gbq1Zs4bOzs7V0jJ27tzJPn36VGuMxeburzWnN2/e0MvLiy1btpQo5ikkJIT29valQleKioqooaHBjIwMfvr0iWFhYXR1daWlpSUDAwO5cuVKtm7dmrq6uhwzZgwTExOr/J4VFhYyPDxcnK29OGj+WwgEAk6bNo2mpqZlmo4ePnxIXV1dmWsM58+fp6urK+fPn19pUPGoUaPYtGnTCvfxykNVcvFFRkaKU0Ll5eWxR48ebN++/X+yH1QR4uLiaGhoyMePH3P48OHs3bt3he/H8+fPqaOjIxVJQ01AJBLx6dOnXLp0Kdu2bUsDAwOxVmhiYsLOnTtz3bp1tLCwkGgRnJ+fz7Vr14o1yq85Y9+9e0dHR0dOmTKF2y4/o+3saFpOP1ZC4H17WE4/RtvZ0dye8Eym9/2fCz6hUMiOHTty+vTpFIlEDAgIoL29fbmTWW5uLkNDQ2lm+YFRxQAAIABJREFUZsYOHTrIJIljXl4eL168yKVLl9LHx4dGRkY0MjKij48Ply5dyosXL1ZIiVZMrrxv375S5MrGxsZicmU9PT1u2bKlXHLl/wp79+6lhoZGqU1okUjE3r17i8mcpcFff/3FqVOnSl3/4MGDNDAwKFNYFBUVcd68eTQyMmJMTEy5bezZs6fCAHVXV1d27dqV2tra7N69O4ODgzlo0CBqamqyS5cujIqKkom2UVBQwI0bN4pXxV+HJLx69Yqenp5s165dhYJt/PjxpeIwq4u5c+dyypQp9PT05PHjx8sde0hICNXU1Ojg4CCVZ+mZM2ckysVXjLNnz1JfX5+RkZEUCAQcPHgwmzVr9l3ibiXB48ePaWBgwLi4OIaFhdHOzk4iD2E/Pz/OmDHjO4xQOhQUFDA2NpZ+fn5s2LAha9WqRQBUVVWlo6Mjx44dy/j4+AqtLbm5uVyxYgWNjIzo6+sr1hbT09Np392P9aYerlDgfXvYzj4hU+FX44Iv7VN+hfbbkJAQenh4MC8vj6NGjWLjxo3LZLHIzs7mkiVLaGRkxO7du1crn9uLFy8YGRnJiRMnskmTJuJUPOPGjasw71ZWVhYTExMZERHBqVOnsnv37mzQoIHE5MotW7ZkXFyc1OOuKRQUFFBJSYm///57qWsfP35kgwYNpGbsGDFihNTZ5/fs2UNDQ8NK6azi4+NpamrKadOmlTLRFE+exftSxcjJyeHff/9NDw8PMX3UH3/8QXNzczo5OXH58uV8+/atVOOuDPn5+Vy/fj3r1KnDzp07c82aNTQyMuL8+fMrDdhPT0+nnp6eTPPUtWzZkgcOHKCamlopjerbfbwNGzawXbt2UvVz4MABdu/evUp1bt68SVNTU65atYpCoZATJkygo6NjpaTdNY2PHz/S3t6ea9as4ZUrV8pkmCoPz549o46Ozv8pUm4dHR0uWLCAHTt2pLGxsdiD1MjIiN7e3ly1alWZC7bPnz9zyZIlNDAwYP/+/Xn44g3afGPWVDFrJOY0LT6U9MzLEH7RvPlCNmbPGhN8N55ncuS2ZDb4/2y1Zdlve62OpaFdYz548IC9e/dmmzZtSu1lZWZmct68edTX15cqNVBBQQETExO5YsUK9urVi3Xq1KGenh67du3K4OBgxsfHl/ixf02uHBoayrFjx4rJldXU1Oji4iImV46KiuKdO3ck1gb69esntQCpSZw6dYouLi40MDAoMzD65s2b1NPTq5RppCx4eXlVqI2Vh23bttHY2Fji7/vdu3ds3749mzdvLtbsysqg/s8//3D8+PHU1dVlu3bt+Pvvv9PKyooqKir09/eXOp2PNCgmWZeXl2fTpk0l5qtctmxZhclcq4Lc3Fyqqalx3759pbSxsvbx7t+/z3r16knV15YtW0oRpUuC1NRU2tjYcOrUqRQKhZw7dy6trKxkRiJfVQiFQnbt2pV+fn589+4dzc3NJaLp+hrDhw8vMzPKjwoNDY0SsahFRUW8cOEC//jjDzo7O1NNTY0AWKtWLTZs2JB+fn6MjY0VL+Sys7P5119/0bTvXFpMPVKm4NNw6yY+tFoNKdPs6be9arlQy4MiagA7ElOx4MR95BcJQZa+nl8kAgAkvcyDRo/Z+G1eGIwKCnD8+HGoqqoCANLS0rBy5Ups2LABXbt2xYULF2BjY1Np32/evEFCQoL4uH79OqytrdG0aVN06dIFCxcuRP369SEUCvHkyRPcu3cPoaGhuHfvHu7fv4/79+9DVVUVtra2sLOzg62tLbp27QpbW1uYmZlBXl5e6udiamqKV69eSV2/pnDkyBH8+uuvqFu3LoYOHYpr165BRUVFfN3R0RGLFy9Gr169kJSUBDU1NYnbTk1NRd26das0nk2bNiEoKAhxcXGws7OTqI6BgQGio6OxZMkSuLu7Y9GiRZgzZw5WrVqFpk2bYufOndi4cSMeP36Mli1bwsPDAxcvXoSmpiamTJmCv/76C8uXL6/SOKuDt2/fYsCAASCJJ0+e4OjRo+jatSvc3d0RFBQEZ2fncuuOGzcO69atw5kzZ9CmTZtqjePy5ctwcnLCxYsX0a5dOwBffnuBgYHYt28f5syZAz8/PygpKQEALC0t8fLlSwgEAvE5SZGVlQUtLa0qj9HCwgKXLl1Cly5dMHToUGzatAlaWlr45ZdfcPLkSdjb21e5zepg9uzZ+PjxI/bs2YOuXbuif//+8PHxqVIb06dPR5MmTeDv7y/VM/neKCgoKDEnKCgooEWLFmjRooX4XEZGBqKionDixAkcP34cmzZtgkgkgr6+PhwdHeHZvjNq1WsAgagMoQBAp+2oCsdAAmcfpOHD5wLoqqtUWLYyyJFliSbp8UXo3UOeQCRxHXlREQK7OWBw83p4/fo1QkJC8Pfff6N3796YOnVquROnQCDArVu3kJCQgMuXLyMhIQEfP35E06ZNxYe9vT1evXqF+/fvi4XbvXv38PTpU5iamoqFW/FfW1tb6OrqyupxlMCKFSuQmpqKVatW1Uj70oAkLCwsEB0dDXt7e/j4+KBhw4ZYsGBBqXJDhw6FSCTC1q1bIScnV2nbQqEQtWvXxsePH8ULmsqwdu1aLFmyBHFxcbCyspLqnqKjo9GtWzf8/PPPaNGiBXbs2AErKyvo6+sjKSkJ5ubmGDJkCPr06QMdHR2QhI6ODu7fvw9DQ0Op+qwKzp49i4EDB2L48OEIDAyEgoICACAvLw9hYWFYvHgxPDw8EBQUBEdHxzLbiIqKwsKFC5GSkiKuLw1mzpwJeXl5HDx4EBs3bsSVK1cQHByMAQMGYM6cOdDR0SlVx8LCAmfOnEH9+vWr1FdgYCDk5OQQFBQk1Vhzc3PRp08fCAQC7Nu3DwcOHEBAQACOHj0Kd3d3qdqsKnbv3o0ZM2YgKSkJISEhuHr1KmJiYqT6DoYMGYL69etj9uzZNTBS2YEkFBQUIBQKJfrdf10vOTkZkZGROHfuHJ6rNYCquy/klUoKrbc7p6HgxR3Iq3xZUCsb1YdWqyFQMW5Qqk1VRXn4t2sAP8+qvXvfQqaC7+aLLPQNT0SeQCg+V/juKTLj/0bhm8dgUSEUNQ2g4doFGi6dS9RVUZSDa9YFxOzciMGDB2Py5MkwNTUtUSYtLa2ENnf16lVYWFjAw8MDjRo1go6ODj59+oSHDx+KhVx6ejoaNGhQQrjZ2dnB2toatWrVktWtS4TIyEjs27cPUVFR37XfinD9+nX06tULjx49gpycHN68eQMnJydER0fD1dW1RNmcnBzxKnX48OGVtv3ixQt4eHhIrOUuX74ca9aswZkzZ2BpaSnN7eDTp0/w8PBAVlYW0tLSUKtWLRgaGiI3NxeDBg3C4MGDYWtrW6peu3btMHHiRHTu3LmMVmUDkUiEhQsXYu3atdi6dSvat29fZrm8vDxs2LABS5YsQfPmzREYGAgHB4cSZUiiefPmGDVqFIYMGSL1mJo2bSr+Pg0NDWFjY4OQkJAyn1Ex2rRpg2nTppU7/vIwceJEWFpaYuLEiVKPt6ioCKNHj8bNmzdx/PhxJCQkYOTIkdi7dy9atWoldbuS4OrVq/D29kZcXBweP36MP//8EykpKdDT05OqvYcPH6J58+Z48uQJfvrpJxmP9ss7IhQKIRQKIRKJqvT56//z8vLwyy+/4OLFixWWK+9zUVER8vPzsf+1Bh4UlL7P91FzAQAKGrooeHUfgrRUyKuqw2TEeiioa5cq7+NsihV9yreISAKZmjrXxj9GfpGwxLn3+/+CMPs9lPQtoaRjgtwHCcg4tR5KumZQtfjfaja/UIjn6ra4f/8+DAwMIBQKcfPmTbEml5CQgHfv3sHR0RHm5uawsrJCnTp18PTpU+zfvx8HDx6EnZ2dWLh16NABtra2sLCwqNaKWJb4EU2dhw8fRvfu3cUrOWNjY4SEhGDo0KFISUmBsrKyuKyamhqioqLg6ekJNzc3ODk5Vdj2s2fPJBZgCxcuREREBM6dOwczM7Mq38fTp08RFhaGlStXQkVFBdbW1vj8+TPq16+PZ8+eYdOmTfj111/Lre/u7o6UlJQaE3xpaWkYOHAg8vLykJKSUmpR9zVq1aoFf39/+Pn5Yf369WjXrh08PT0RGBiIhg0bAgDk5OQQEhKCXr16oVevXlUyPxfj06dPuHnzplgTW7NmDby9vSutV79+fTx58kSiPr6efNPT02Fra4uPHz9KNOGW93no0KEIDw+Hi4sLFi1ahClTpqBHjx4YP3483N3dq9V2eXU+fvyIbdu2oVWrVli2bBmioqLQpUsXzJo1S+p+ijUoBwcHGBkZVVkgVfaZJOTl5aGgoAAFBQWJP8vJyYkPkuJ2i03zxeeK/xZf/7r/oqIi8d+ioiIoKChAr+dsqNZ3K/WO6PvOEc8/FArwaqMfhNnvkf/8FtTsW5Yqn50vkOjdqwgy0/jSPxeg+eIzKCj6n4mTwiI8X9YToAjGw9dAWd8SbyImovDtY+h2mgB1x3Yl2lCUA3zkU5B88SySk5OhqakJAwMDKCoq4uPHj3j58iUMDQ3FWtvXGpyenl6V1PD/Ak+fPkWbNm2Qmpr6Xw9FDBcXF6xcuRKenp7icyTRtWtXuLm5lWmW2rVrF4KCgpCSklLhSnXbtm04deoUduzYUW4ZkuL9pLi4OBgbG0s89qKiIhw7dgwbNmzAlStXoKSkhIyMDDRt2hRDhw6Fr68vfvrpJyQkJKBv377o2rUrFixYIDbbfP1DPXr0KHbv3o0tW7ZItSqu6PM///yD0NBQNGvWDD169ICcnFyVV9wpKSlITEyEmZkZPDw8oKWlBaFQiOjoaGhra8PZ2blKk2JeXh7u3LmDzMxMqKmpQV9fH/r6+hKNJysrC0KhEGpqapXeAwDxxCoUCqGkpARlZeUKJ19JJ+m3b9/ixYsXcHJygry8PK5fvw57e3uYm5tLVF/Sfkhi06ZNsLOzQ6tWrbBq1Sq0adMGLVq0qHbbz58/x8SJE7Fv3z5oaGhILJzk5eUhFAqRn5+P3Nxc5OfnIy8vD7m5ueIjJycHOTk5+Pz5s8RHYWEh1NTUoK6uLj6UlZVx7do19OjRo8R5SQ81NTXIyclh8IYzuPCioMRvWCTIhyg/B4oaX7aXvhZ8et2nQs3ul1K/e1lofDITfBvOPcGK0w9LCD4AyIgLx6fkwyU0PiUDSxj1D4a8qnqJsiwqQH7SPmQl7ke9evXQqFGjEsKtQYMGUq1sfwSQRE5ODnR0dJCZmSkzM0R16qSlpWH+/PkIDg4GgBLXMjIysHr1agwePFisgX9d/9SpU8jLy0P79u1LrPq+Lnfjxg2IRCLY29uXO56HDx/iw4cPaNSokfjHXNm4CwsLkZ2djZycnBLPFwBUVVVLrFK/nny/LqOoqFhiQgGADx8+wNTUtEoTV0XX5OTk8OTJEzx69AhNmjSBmZlZtdoWCARISkrChQsXYG1tjY4dO0JZWRlLlixBUFAQdHR0Km1bJBLhxIkTiIyMhIGBAdzd3XHy5EmsX78e5ubmEo0tOjoahw8fRkREhET3U4xWrVohKChIpibJgwcPws/PDzt37oSpqSk6dOiAqVOnYty4cTJpv3hvOycnB3v27BHvC4eFhVWpjdzc3HKFzZIlS2BiYgIPD48qCSkA0NDQkEoYlXfUqlWrlALx8uVLeHh44OXLl1V6du/fv8epU6cQExODU6dOQdPDF0J7b4jk/meBK8p6h1fhflC1cILiT/r/M3WqacFk+Foo1NYs0aas9vhkZuq8/za7lNADgNrWTZH7MBGCtFQI0lIBeUXUtvaAnHLp/TU5RRXYNWuHTp2dS6yKnzx5gocPH9aYAJBVnYquARBPPHp6elKtDmVd5/79+zAxMcG9e/fKrNO6dWscOHAAI0aMKLVK79evH0JDQ/Hu3Tu0atWqzH7//fdf2NnZwcvLq1Tb8vLyCAsLg4qKCnbu3AkdHZ1KJ89Lly5h165dSE5OhpaWllgzNTU1xa5duxATEwNLS8sy+wK+TECrV6/GggULsG7dOvj6+orfPZIwMjLCpUuXpDK1fosPHz7gt99+g4aGBh49eiSTNovx6dMnrFmzBitWrECHDh3Qt29fPHz4EOHh4eXWIYmjR49iypQpsLGxwZUrVzBgwAB4e3sjMTERvXv3lrj/Jk2aYP369TAyMqrSuKX16qwIPj4+0NfXx6+//orly5fj/PnzaNeuHTIzMzFr1qwqW4GEQmEJLWnDhg24dOkSFi9ejMGDB+Pq1asYN24cFi5cWK5A+vTpU4n/c3JyoKqqWq6wMTAwwMmTJ2FpaQltbW2YmZlJJKS+3oaoSXzr0VkeioqKkJSUhOjoaMTExODRo0do06YNvL29MWvWLOw5dBx/fxBCTvF/gk++lgbUG7VB/r+3UPD8NuRUaqOWtQe0PAeVEnrAlyA/X5c61b4nmQm+7PyiUueEedl4HxUICgpgOGAxlPQt8D5yNj5e2g0FNa1SDi4A8O/r99h2dDtq166NWrVqoXbt2uKjWAVXU1ND7dq1S63av6fQqGqd4snXwcEBO3bsqHR/7HugXbt2mDx5Mnr27FnmdZLo2LEjVFVVMWvWrFLXfX190axZMwQEBIi96tI/F2Df1Ze4/zYbaXa/wsS+ATIMG6CXax2xC7JIJMLvv/+Ot2/fIikpqcLJ8PXr19i8eTPWrl0LkUiEnJwceHh4YPjw4ejRoweSkpLQu3dvnD59upQDyLeQk5PDhAkT0KxZM/Tp0wdnz55FSEgIVFVVIScnJ97nq66QKjat9urVC8HBwVV2+68MGhoamD59OsaOHYvQ0FAsX74cubm56NGjR5l7lLdv38aff/6JV69eYc2aNejQoQMyMjLw6NEjvHv3ThzGICnq16+Pp0+fgmSVBIusBV9hYSE+f/4Mc3NzhIeHY9SoUejRowdmzZqFOXPm4Ny5c/D29q5Q2/r2KCgoEM8zcnJyeP/+PX7++WcsXrwYN2/eRLdu3fDvv/+KhY+RkZFEpr5iq0J58PX1hbm5Ofz9/WX2fGSF/Pz8cgXf69evcfLkSURHR+P06dMwNzdHx44dsWzZMjRt2hQCgQDr169Hq1at4OLiAmVDIQSGdoDcl/lQXqU2dDuOl2gccnJAaxv9aocyADI0dU6MvI5DN16XOFfw5hHebvUH5BVh/mcU5BSVkH5sOXLunIGGSxfotB9dqh1z4Rt00kkHSWRlZSEjIwOZmZml/ubm5kJLSwva2trQ0dGp0t/v7c35Nby9vTF+/Hh06tTpPxsD8GUSMjc3x+vXr6Gurl5uuRcvXsDFxQVnzpwpU7Ds378fkydPxvbj57Dt6nuce5gGACW0f1VFeRBAKxt9jP6lHlYHTcKTJ09w/PhxaGholGpTJBLh9OnT4hW8kpISdHV14efnh4EDB4odQ+7cuQMvLy/s3r27yvFsWVlZGDFiBJ4+fYrIyEhYW1sjKCgIhYWFWLhwYZXaKgZJLF++HEuWLEF4eDi6desmVTtVxcePH9G/f3/ExsZiwIABmDVrFurXr4+0tDTMmTMHBw4cEMfjKSp+WesWhy/Iy8tj2LBhJbRfSaCnp4c7d+5IpPWRRF5eHoyNjXHu3DnIy8tXyaRX3kGyhKlPSUkJjx8/hpGREZydnXHx4kXo6enBx8cHP/30U5VMfQ8ePMAvv/yCAwcOwMLCAo0bN8aOHTvg5eUl1XdUGW7cuIFOnTrhyZMn/+n8VBauXbuG4cOH4/r16ygsLMTly5cRExOD6OhovHjxAu3atUPHjh3Rvn17mJiYAPgSerJhwwYsXboUzZo1g5WVFTZv3gy/GQuxP8sM+VUIdytGLSUFRI7ygGOd6i+eZKbx2Rr9BBXFtyUmPCVdM8irakCU/wnv9syEopYRcu6eBwComJUOOhUJCnA/+QyuXT0CJSUlNGnSBM2aNUPPnj3h7u5ewm1YIBBUKBifP3+OmzdvlnldXl6+UgFZ1jktLa1KV26VwcTEBK9fv668YA0jJiYGv/zyS4VCDwDMzMywYMECDB06FImJieKJsxi//vortl5+hkFbrwEKShUSFpy6+w6xt19BN18L8dHRpfZr379/jw0bNmDNmjXIy8sDSQwcOBAjR46Em5tbCe3i5cuX6NSpE1auXClVELeWlhaioqKwbt06NGvWDKGhoXB3d5c6xjIzMxNDhgzB27dvceXKFanDMaSBpqYmDh48CHt7ewgEAjRu3FjseTlo0CDcv38f2tol3cLPnj0LT09PLFq0qITz0bemvvKOWrVqISAgAFpaWpWWzcnJgbKyMvLz8+Hj41PpvlSdOnWkNvVlZmaiW7duUFFRwb1799C3b1/cvXsXu3fvlshc93UbwcHBcHd3h6enJyZOnFhjQg8AnJ2d4e7ujs2bN8tsf1JW+Pfff5GVlQUfHx+cPXtWvL+8fv16NG7cuMSckJeXh40bN2LJkiXw8PDA5s2bsXTpUly4cAEJCQmwtraGnRSx3rWU5DGzk61MhB5Qw16dAFDw+gGyzm9H4dsn4jg+dWdv/OTevVQbKoryWNVGA1fOxyE6Oho3btyAvr4+lJSUkJaWBn19fbi7u6Nx48Zwd3eHi4tLpRP3tyhefZYnMCv6m52dDXV1dam0zGLTyezZs6GoqIjAwMBqPe/qol+/fmjdujVGjaqYLQH48szat28PLy8vTJs2rcS1HYmp+OvEvSqt4FSV5DGrkx0GeliCJOLi4rBgwQJcvnwZJOHh4YEJEyagS5cuZU5WWVlZ+OWXX8TxntXF9evX0bt3b3h4eOD48eP48OFDlUx4ycnJ6N27N7p3744lS5Z8t72XYlNf8XHs2DGEhIQA+GLWzc7OhqOjI5o1awZFRcUSZU+dOgUDAwO8ffsWRkZGZZr6Kjri4uJgb28vXjxVZur79OkTLC0tkZWVVePPJS8vDwMGDEB2djZ2796NMWPGICsrC4cOHap0vigqKkKXLl1gY2ODVatWYfTo0UhLS8O+fftq3Gs8JSUFPj4+ePz4scRCuiaQn5+PCxcuiLW6169fQ0VFBcuXL0e7du1gYGBQZp1i8gV3d3cEBgYiOTkZM2fOREBAAP78888SSkMxu1eeoAhA+c9VTg5QVVTAzE62GOhhKbN7lGkA+6jtKYi9967MVX+lAwHRvqERNg78X5xHTk4OLly4gLi4OMTGxuLx48ewsrKChoYGPn78iCdPnqBevXpiQeju7g4HB4cam3iK43mqKjAzMzNRUFAAbW1tsXehm5ubxNqmrO+nsLAQhoaGuHv3rsThA6mpqXBzc8P58+fFFFFlERYUI+fuOaQfWQoA0HDrVoqOSFVRHp6Cq9gfvgLZ2dkwMjLC77//juHDh5f5wypGQUEBOnToACcnJ6xcuVJmk1F2djb8/Pywf/9+HDt2TKLgbJIIDQ3FX3/9hfXr15cbJ1i82JKFea88U5+ioiLS09ORk5MjJnVQUlLC/fv3cevWLTg6OqJr164wNzdHUVERJkyYgB49ekBVVRXTp0+v0KuvLMyePRvy8vKYO3euRM83NTUVrVq1+m6hPEKhEOPGjUNiYiKOHj2KwMBA/PPPPzhx4kSZbDTFmDRpEm7duoXo6Ghs374dS5YswZUrV2okwLwsdO7cGV27dsXo0aW3gWoSjx8/RkxMDGJiYnD+/Hk4ODjA29sbHTt2RFpaGlasWIFTp06Vqpefn49NmzZh0aJFcHFxQVBQEAwMDDBixAikp6dj69at4tjTb3HzRSZ8Zm6AgpkjFOTlxZYh4H/bI61t9PF7KyuZaXrFqHHmFolRVAirf49i28q/xHbib5Geno6zZ8/i9OnTiIuLQ3Z2Nn7++Wfo6+ujsLBQTEXm4OAgFoaNGzeGtbV1tTg2ZYHCwkJkZmYiKioKu3fvxvTp0yUWmioqKlJpmZqammXed2xsLGbPno3ExMQq3cO6deuwbds2XLp0CQoKCuUudIqy0/Fm81iIBPmASFim4KNIhIInSWit9BjTp08vl5rra4hEIvTv3x9CoRB79uypttn5W5CEi4sLHj16hODgYHh7e5frsZeeno69e/ciIyMDnp6eFe5b5eTkQEVFRaZu58Wmvm/38VxdXdGzZ088ePBAvH/64cMHhISEYOPGjejduzcaNWqEU6dO4c2bN1iyZIlU4QURERE4ffp0hTGaX+PGjRsYMmQIbty4UeW+pAVJLFiwAFu2bEF0dDTCw8Nx8uRJnDp1qswFX0REBBYsWIArV67g2bNn8Pb2xvnz5yXmi5UFEhMT0adPHzx69KhGLQe5ubmIj48Xe2Dm5OTA29sb3t7eaNu2bYnFwZEjRxAeHo6jR4+KzxUUFGDz5s0IDg6Gk5MTgoKC4Orqiu3bt2Py5Mn4448/MG3atAodu27evIkePXog+dY97L/+CvfffEJ2vgA/qSrB1lgDvi51ZOLIUhZ+CK5OVUU5TO3QAE9PbsXGjRuxbNkyDBo0qNKVZ2pqKuLi4sSHuro6PD09YWFhATk5Ody9exfJycnIyMiAq6trCWFoamr6nwS8p6SkYNSoUbh27ZpE5Uni8+fPUmmZnz9/xk8//VRKIP7zzz/Q09NDly5dytU2y1r5i0QieHl5oXPnzhgy+o8yTdsk8X7PTAhzsqCkb4HcexfKFHzAF9P25altJH65J02ahOTkZJw6dQqqqqoQCAQy16Ly8vKgoPAlaFlNTQ1169Yt5RiRm5uLkydPwsbGBr169RKbsqvj1VdVFBYWIjQ0FIsWLcKAAQMQGBgo3scbNGgQLC0tMX/+/BJ10tPTsWzZMqxcuRLOzs64c+cOPnz4IJVZ7cKFCwgICEBCQoJE5ePj4xEUFIT4+Pgq91VdbNq0CbNnz8bBgwcRFxeHLVu2IDY2FvXq1ROXSUhIQPfu3XHu3DkYGBjAzc0NS5YsQa9evb77eDt06IBevXphxIgRMmuTJO7fvy/W6i7p9zkPAAAgAElEQVRfvgxXV1d07NgR3t7ecHR0LHc+jIqKEtMtFhYWYsuWLVi4cCEaNWqEoKAgNG7cGO/evYOfnx+ePHmCbdu24eeff650TDNmzIBQKMTixYtldp+SQuaCD6g8O4O4czlAgSIo3DqMpF0h0NTUxLVr1zB06FDUqVMHYWFhFVI7fQ2SuHPnDuLi4nD69GlcuHABdevWRdu2beHm5gZlZWXcuXMHSUlJSE5Ohry8fIn9Qnd39wpNILLC69ev4eLigrdv39Z4X0VFRfj48WMJgZiRkYFx48ZhwIABUFJSKldwkixTi5SXl0dkZCS8/ZfhFs1RxJI/luykQ8g8FwHj35YjO/kwcu7ElSv4lOQBb9MiNNbIrlQgPX78GO/evYO+vr7YPV0kEsk8gPfixYtYsGABjh8/jjFjxuDatWvYu3cvGjZsCJLYuHEjZs+ejTVr1qBPnz41/h1+i+J4vEmTJsHGxgbLli0rxav5/Plz/Pzzz7h58ybq1Ckd81SvXj2Ym5vj8uXL8PPzw/Tp08u1spSH169fw9nZGe/fv5eo/KFDhxAREYFDhw5VqR9Z4ejRoxg2bBi2bt2K1NRULFy4EDExMWjUqBFevnyJJk2aICwsTGzec3JywtKlS/+TsV66dAmDBg3CgwcPqhUK8+nTJ8TFxYmFnUgkEgs6Ly8vic23O3bswLFjx9CmTRssWLAAdnZ2CAoKgoeHB4AvgvGPP/7AsGHDEBgYKNFCiiSsrKwQFRUFFxcXqe9RWtSI4AOAWy+zsC7+Mc4+SIMcUK79dkzL+ghfPBsPHjzAiRMnoKSkJHYpL2bqHzJkSJW1M4FAgOTkZLFZ9OrVq3BxcYGXlxe8vLxgbGyM69evIzk5GUlJSbh69SoMDAxKCEIXFxfUrl1bps9FKBSiVq1ayMnJkXl8lyT4lpS6POTl5SEzM7NMwRgTE4O7mu5QqN+0RJ3CtFS8ifCH1i8DoOnhi/RjKyoUfACg8/ERGn2+VqEwSklJwcaNG7Fz5040aNCgRgN4MzMzYWFhgczMTMjLyyMiIgIBAQGYO3cuLly4gLt37yIqKgoNGpRmjq9p3L59G/7+/njz5g2WL1+ODh06lFt2xowZePXqFbZu3VrifHF4Ss+ePWFqaors7Gz8/fffGDhwIKZNmybxnm+xRvzu3bsyQ1K+RUREBOLj4xERESFR+zWBhIQE+Pj4YNGiRVBWVoa/vz/27t2LSZMmoXfv3ggICMDMmTORkJCAU6dOlfJg/p7w8vLCoEGDMKQKBOQkcfv2bbFTSkpKCpo2bSo2YdrZ2Uk1j44YMQIHDhxA06ZNERQUhGbNmgH4YkIfO3Ysbty4ga1bt6JJkyYSt5uSkoJ+/frh4cOH/w3VpDRJ/KqC9E/53HDuMSfuuc5hEUmcuOc6N5z7XwZ28ktSw65du3LIkCElMp9fv36dzs7O7NChgzi5qLT4/Pkzo6OjOXnyZP7888/86aef2KlTJy5fvpw3b95kYWEh//nnH0ZERHDs2LF0d3dn7dq16ejoyBEjRnDjxo28du0aCwsLqzUOkjQxMan2/UiLwMBA/vnnn9VqQygU0mbkilKJIjVb9CcgR9V6rqxV350KGnoEQEVNQ/7k4VuqvMW0YxwWkVRhX/Hx8WVmUK9J1K9fv0TS3f3791NZWZlWVlZ8//79dxtHMd6/f8/Ro0fTwMCAa9asKZVlvix8/PiRRkZGpZLbbt26lb169WK9evXESX7fvHlDf39/amtrc+LEiRJnN2/YsCGvX78uUdkVK1ZwwoQJEpWtSdy7d4+WlpZcuHAhDx8+TBUVFXp5eVEkEvHQoUM0MzMrM5P490Z8fDytrKwq/a4zMjK4d+9eDhs2jCYmJqxXrx7Hjh3LY8eOlUiwXVUIBAJu2bKFdevWpY2NDbt3717i+pEjR2hiYkJ/f3/m5uZWuf3Jkydz5syZUo+vuqhxwScpPn/+TFdXV86dO7fE+cLCQs6bN496enoMDw8vIRirg7S0NO7du5d+fn6sX7++OMN7eHg4nz59SpLMz89nUlIS165dy8GDB9Pe3p5qamps2rQpJ0yYwB07dvDhw4dVHpObmxsTExNlch9VhbOzM8+dO1ftdoaFnSst+Jr3I76wCpU6VMwalSn4hm86X24ft2/fpoGBAePi4qo93qqgb9++3Lp1K0UiEcPDw6mnp8dNmzZx6NChtLGx+W5CuKCggMuWLaOenh4nTpzIjIyMKtVfv349W7VqVeL9HDx4MOfNm0cjI6NS7+3r1685fvx4amtrc9KkSZUKgG7dunHfvn0SjSUwMJCBgYFVGn9N4dWrV3R0dKSHhwcbNGhAfX19rlmzhvr6+v/Z77IseHp6cvv27SXOCYVCpqSkcP78+WzevDk1NDTYqVMnrl69mo8ePap2nwKBgBEREaxfvz5bt27Nc+fOcfny5Zw4cSJJMisri0OGDGHdunWlnkeEQiHNzc3FC6//Aj+M4CO/rDwtLS25devWUtdu3bpFFxcXtmvXjqmpqTLvOzU1lZs3b2a/fv1oYGDAevXqceTIkdyzZ0+JVX52djbPnj3LJUuW0NfXlxYWFtTS0mK7du04Y8YMHjx4kK9evaqwr+7du3P//v0yv4fK8O+//1JXV1cijaEyrI9/zHrTjpQpzIoPtUZeBEANt25lXrcMOEQTr99oZWXFcePGlVilvnjxgmZmZty5c2e1x1pVLFu2jH5+fhw0aBAbNmzIu3fviq9t27aNenp63Lhxo8wWYd+iWPuwsrJi586def/+fanaEQgEtLe355EjR8TtmpubMygoiAMHDiy33suXLzlu3Djq6OhwypQp5Wq5/v7+XLx4sURjmTBhAlesWFH1m6gh7Ny5k8rKyuzcuTNjY2OpqKjI33777b8eVgmcPn2aNjY2fPv2LXfu3MmBAwdSX1+ftra29Pf358mTJ6XStsqCQCDgtm3baG1tTU9PT549e1Z8LTg4mFOnTuXJkydpZmbG0aNH89OnT1L3denSJdrZ2dXY70cS/Lc+/t/AyMgIx48fx5QpU3DmzJkS1xwcHJCYmIhWrVrB1dUVGzduFLPtywIWFhYYNmwYdu3ahbdv3+LQoUOwt7cXZ+92dnbG5MmTcfHiRbi5uWHKlCmIiopCamoqHjx4gAkTJkBJSQlhYWFwcnKCqakpfHx8sHDhQsTGxiIzM1Pc13/F3nLkyBF07txZJnsXvq51qt2OSCTCgKb1sXHjRtSpUwfLli2DkZERWrZsCXd3d/Tq1Qv9+vWr9lirCj09PWzduhUKCgq4cuVKCXf2QYMG4cKFC1izZg369++P7OxsmfZ969YttGvXDjNmzMCaNWtw7Ngx2NjYSNWWoqIili5diilTpkAgEODp06coKioS91EeTE1NERoaips3byInJwe2traYNm0a0tPTS5SrSl6+miColhZ37tzBxIkTERcXh9q1a6N///7o0KEDzp49KzVzjywhFAqRkJCAc+fO4dWrV6hbty727t2L5s2bIykpCffu3cPy5cvRvn37atObCYVC7Ny5Ew0bNkRYWBg2bNiA+Pj4EiEu2dnZOH36NEaMGIFNmzZh/fr1VSYO+RqRkZHo06fPf5tG7j8TuRXgzJkzNDAw4J07d8q8fufOHbq7u7NNmzZis2RNorCwkJcuXeK8efPo6elJNTU1/vLLLwwKCuLFixdL7fuJRCI+ffqUkZGRnDx5Mj09Pamurk5ra2sOGDCAnTp14sCBA2W2WpMUbdu2lammOXJbMi0r0PgqOiynH2P/dWfp5+dHLS0tjhw5kvfu3WNaWhobNWrERo0a0cLCgqamphw+fDijoqKqbOqTBhEREdTV1aWysnKF+7m5ubkcNWoUrayseO3atWr3++7dO/r5+VVpH08SiEQienl5cc2aNQwLC2P//v2pra1dqVXiazx//pyjR4+mjo4Op0+fzvT0dJJkdHQ0vby8JGqje/fuPHjwoFT3IEukp6ezXr16YhPismXLqK+vz0aNGjExMZHW1tacM2fOd9dG3rx5w7///pt9+vShjo4OHRwcGBAQwMWLF9POzo5CoVCm/RUVFXHXrl20tbVls2bNGBsbW+Y9nzt3jlpaWnRxcWFmZqZM+jU2Nua9e/eq3VZ18EMKPpLcvn07LSws+Pr16zKvCwQCLl68mLq6ulyzZo3MX4yK8PnzZ8bExJTrKFPWWIqKinj79m1u2bKFrVu3pq6uLmvXrk1nZ2eOGjWK4eHhvHnzpswmvG+RmZlJDQ2NapkovsWN55m0nR0tleCznR3Nmy++/JDev3/PuXPnUl9fn8bGxvT09KRAIKBIJOKDBw+4atUqduzYkerq6mzWrBnnzZvHpKQkmX7nOTk5HDZsGG1sbHj79m3a29tLJNB2795NPT09rl27VqrJsrr7eJLgxo0bNDAwoK+vL2fOnEl7e3up2klNTeWoUaOoo6PDmTNnMikpiZaWlhLVbdmyZQnz2X+BwsJCtm7dmgEBASS/OJAYGBjw6dOnXLRoES0sLHj+/Hk6OTnxjz/+qNE5pbCwkOfOneO0adPo7OxMLS0t+vr6cvPmzXz58qW4nEgkYuPGjRkVFSWTfoVCIffs2UM7Ozt6eHjw5MmTZb63ubm59Pf3p7GxMbt3785ly5bJpP/4+Hg6OjrKpK3q4IcVfCQ5b948uri4VDhZ3717l02aNGHLli35+PHj7zi6/0ESR5mvERMTw7Zt2zIvL4+JiYkMDQ3loEGDaGtrSzU1NTZv3pz+/v7ctWsXHz9+LJPV5+7du9mpU6dqt/Mttic8o/WMqgq9E9ye8KxUWxMmTKC1tTWtra3p4uLCnTt3ltC6cnNzefLkSfr7+9Pe3p56enrs378/t23bxrdv30p9D/fu3WOjRo04YMAA8bs2ePBghoWFSVT/4cOHdHZ2pq+vL7OysiSqI6t9PEkxZMgQqqmpcdKkSdX2rnz27BlHjBhBHR0dKigoSPTsnZycJPYArSmMHTuWnTp1YlFREV++fEljY2OePHlSfD0iIoKGhoY8efIkmzdvzkGDBsl0Ifr8+XOGhYWxZ8+e1NLSoqurK2fOnMmLFy9W2M+xY8fo6OhYLUEsFAq5d+9eNmzYkI0bN2Z0dHS580piYiJtbGzYp08fpqenc+zYsQwNDZW6768xZswYLliwQCZtVQc/tOATiUQcNmwYu3TpUuGLUVRUxKVLl1JXV5erV6/+rtpfWajMUeb27du0s7Mrs25WVhbj4uK4aNEi9uzZk2ZmZtTR0WH79u05a9YsHj58+P+x951hTaVd13GsdEIaIfRepEpTUAELIoKgoogijhTHigqoiL2ggFJEEHkcLFhQsaLoWMau2MWxd3SwgwWk56zvB1/yEpOQis48j+u6+MEp9zlJzrn3vvdee22x6eYtERwcjHXr1sn60fhQW1sLQ+8wGM0+AN2ZrZNddGcegNlcwUYvLS0NFhYWqKioAJvNRlFRETw8PKCjo4OVK1cKNChlZWXciURNTQ329vaIj4/H6dOnxS472bp1K6hUKnJzc3kmgszMTERGRkr0PUyaNAmGhoa4fLn1Eo3S0lL06dMHlpaWOHLkiNjXkAUnT57EL7/8AldXVxw8eFAuYz558gTKyspQV1fHggULWg2F6enpfZe0hDDk5OTA3Nwcnz59Qn19PVxdXbF06VK+44qLi0GlUrFz504MGDAA/v7+qK2tleqadXV1OH78OGJiYmBlZSW1o0YQBBwcHKQKFbPZbBQWFsLa2hqOjo44dOiQUINXV1eH+Ph4MBgM7Nixg7s9IiJCbCewNTQ2NoJOp/+wBUpL/KMNH9AcEujXrx8mTpwocuVz//599OjRAz179sTDhw+/0x22DoIgcOvWLaSlpWHQoEFQVVVF165d0alTJxQXF4sVenz9+jUOHDiAefPmwdvbGxoaGtDW1saQIUOwfPlyHD9+vNWVRn19PdTV1YWGjWXB3LlzMWTIEJS+/IjeCVugP3MfzOYW8xg8s7nFMJ1bjG7RORgXu4hvjB07dkBbWxtlZWV8+65evYqRI0dCQ0MDM2bMEHgM0PycnD17FgkJCejWrRvU1NQQEBCAnJwcgSzg2tpabo5O0EqkpKQE9vb2En8fu3btAo1GQ3p6Ot/z2jKPl5WV1WZhbUFYs2YNbGxs0KFDB7mGu/v06YPff/8dY8eOBZVKxeLFi/H582e+49TU1L5LjlYQOCFNzpwwadIk+Pv7C3WQL126BE1NTWRnZ2P48OHw9PTEly9fxLrWkydPkJWVhUGDBkFFRQWurq5YtGgRLl26hKamJqk/w759+2Bvby929IcgCOzZswe2trZwcHBAUVFRq+feuHED1tbW8Pf35zPKoaGhApn2kuLYsWPo1q2bzOPIA/94wwc0r4Ksra2RkpIi8timpiakpaWBQqEgNTVVpoetLdDQ0IBz586hQ4cOcHNz4yHKnD17VqyVCkEQePz4MbZv344ZM2bA3d0dysrKMDMzQ2hoKFavXo2SkhKup3r06FG4uLjI/bP89ddfoFKpXKJEQ0MD7FzcMS5lm0DBgtevX4NCofCUB3AK1G/evNnqtcrKyhATEwMNDQ2MHDkSV69ebfX4t2/fIj8/H6NGjQKVSoW5uTmmTZuGI0eO4K+//oKdnR2GDx8ucJIGmg2jgoKCVN7+kydP4OjoiICAAFRWVn6XPJ4oDBkyBNHR0ejUqRMuXbokt3GjoqKwZs0aAMCjR48wZswY0Gg0LF26lPvdstls/PLLLz/kXXz69CkYDAaOHj0KAFzKvqiQ9MOHD2FoaIgFCxYgMjISTk5OXFJPS9TU1KC4uBhTp06FqakpGAwGwsLCsH37doHHSwuCIGBra4uioiKRx+3btw92dnaws7PD/v37WzV4nDppGo3GrV39FkFBQSgoKJD5M0RERCA5OVnmceSBf4XhA5rj49ra2ti5c6dYxz98+BDu7u7o0aNHm+dPpIGhoSEePnwolCizatUqoUQZQWhsbERpaSnWr1+PqKgo2NvbQ1FREQ4ODrCyssKQIUPw119/yW3yaWpqgqurK3Jycni2l5aWgkql4uXLlwLPS01NRd++fUEQBLdA/fjx42Jf99OnT1i5ciV0dHTg4eGBoqIikd8Rp+h36dKlMDc3B4lEgoWFBVJTU3Hv3j2hE4O9vb3UBc11dXWYOnUqaDQatLW1MWjQoB/2HLLZbGhoaCAyMhIBAQFwc3OTG2sxKSkJ06dP59n24MEDbs1ZYmIiXrx4AVVVVblcTxJUVVXB2toaGRkZAJpXNVQqFX/99ZdY579+/Rr29vaIiopCXFwcLC0t8fLlS9y/fx/p6enw9vaGsrIyevbsicTERFy/fr1N0yyFhYVwcnIS+NsRBIEDBw7AwcEBNjY22LNnj8jf+M6dO+jWrRv69+8v9H0FmoUKZGXkNjQ0gEKhtEkNtjT41xg+oPnBpdFoOH/+vFjHs9lsZGRkgEKhYOXKlf+o1Z+7uztOnTrFt10QUWbEiBFCiTKtoaamBufPn4e6ujp8fX1hamrKfVFjYmJQUFCAp0+fSjUJZmZmomfPngJf9IULF8LHx0fguA0NDbC0tERubq5MBeoNDQ3YunUrHBwcYG5ujtzc3FZXZ3V1dZg8eTIMDQ1x8uRJFBYWIiIiAtra2tDT08P48eOxd+9enhVgZGSk1En90tJSeHl5QUdHB2pqakhJSflhuecbN27AzMwMXbt2xfnz52FjYyO24oooFBYWwt/fX+C+e/fuISQkBBQKBerq6nINsYoCm81GYGAgwsPDQRAEKioqYGhoiO3bt0s0zpcvX+Dp6QkXFxc4OzujQ4cO0NTUREREBHbv3i02mUkeYLPZsLKywuHDh7nbCILAwYMH4ejoiK5du6KwsFDkc9bU1ITk5GSxhRi8vb1RXFws070XFxfD1dVVpjHkiX+V4QOaa4c0NTUlyuE9fvwYvXv3hqurK0+Y7UdixIgRYk363xJlDAwMBCrKCMP169dhZGTEfbg/fvyIY8eOITExEQEBAWCxWKBQKPDx8cH8+fNRVFQkMvH+4sULUKlUobU49fX1sLGxwcaNGwXu379/Pzp27CiQXCApCILAyZMn4evrCwaDgYULF/J9L5zQY2BgIB8BgyAI3LlzB6tWrUK/fv2grKyMXr16ITExEXPnzpVYzePt27eIioriyeM9f/4cLi4u8PX1lWv4S1ysWrUKYWFhUFdXR1NTE44ePQojIyPU19fLPPaNGzdgZWXV6jGFhYVQU1MDg8FAcnKyTBqS4mL+/Plwc3NDXV0d2Gw2fHx8uLJbosCJRiQnJ8PLywtKSkpgMBjQ19dHXFwcmEzmd9WObYmCggK4urqCzWajuLgYzs7OsLKyws6dO8VyrB4+fIgePXqgd+/eYjvSHh4eMssGhoWF/aOUe/51hg8A1q1bB2NjY7x//17sc9hsNrKyskChULBixYrvSiwQhOnTp4uVs2wJzgvZkihja2uLGTNmCCXKiCNKXV5ejn379iEhIQH9+vUDmUyGrq4uhg0bhqSkJJw8eZKb3CcIAn5+fnyaqt/i+vXroNFofIXSdXV18PDwgLGxMebPny/R5xeFu3fvIjIyEurq6hg/fjzu37+PPXv2CCWbCEJ1dTUOHTqEqVOnQldXF+3bt8eYMWOwdevWVp+3uro6LrNYUB6voaEBsbGx0NHRwdmzZ2X+rJLA19cXkydPRmBgIHebj4+PXCaiL1++QEFBodXv9uTJk+jVqxdu376NoKAgMBgMrFy5El+/fpX5+oKwc+dO6Orqch24+fPno1evXq3mzz9+/IjCwkKEh4eDxWLBwMAAEydOxIEDB1BVVQU2m42YmBhYWlpizZo1oNPpuHDhQpvcf2tobGyEjo4OLCwsYGFhgYKCArEMHpvNRmZmJigUCtLT0yWKPnTv3h3nzp2T+p7r6upAJpN56hN/NP6Vhg8AZs+eje7du0usfvL06VN4eXnByclJqDLM98DKlSvF9kCFoaWiTO/evaGkpAR3d3ceoow0otQEQeDhw4fYunUroqOj0aNHDygpKcHCwgK9e/eGpqYmzp8/j7q6ulbHmTt3Lvz8/LiTIpvNRnBwMIYOHYqnT59CQ0OjTSjub9++RUJCAhQUFKCgoICcnBypwrkNDQ1QUFBAamoq/P39oaqqCicnJ8ybNw/nz5/nFtlz6vHEyeMdPHgQDAYDy5cv/y6hz8bGRqipqSEoKAjZ2dnc7bdv3waNRkNFRYXM1xDk4LTE3r17ecKht27dwtChQ6GpqYnU1FS5Khhdv34dVCqVKz5QVFQEFovFVwLEZrNx7do1LFu2DD179oSysjIGDBiA9PR0PHjwQOjzwskvZ2dng0ql8tQBtiUIgsCxY8fQo0cPMJlMmJmZie28P3/+HJ6ennB1dZUqz+zg4IArV65IfB4H+/fvR8+ePaU+vy3wrzV8nEk0KChI4gmEIAjk5OSAQqFg2bJlP2T1t23bNgwfPlyuY3KIMnFxcbC3t4eysjI6duyI5ORk3Lx5U6aJlqM0oaamBj8/P9ja2kJRURGOjo6YOHEiNmzYgDt37vDkUevq6mBlZYUtW7YAAGJiYuDu7s7NxS1ZsgQBAQGyfWgB4IQWOSQhExMTODo6Yvv27RL/1i4uLlzHob6+HidPnsSsWbNga2sLFRUV0Ol0aGlpcT+jOHjx4gXc3Nzg7e3d5i1wSkpKYGNjAyaTyafeP378eD5iijRwdXXFmTPCu2xs2LBBYMj45s2bCAwMBJPJRHp6uswG8M2bN9DV1eUS4B49esTDCfjw4QO2bduGMWPGgMFgwMzMDNHR0Th8+LBE1966dSvodDpWr14NGo0mN1UVQSAIAidOnIC7uztMTU2xZcsW1NXVwcTERKQSTsvuIitWrJCa42BlZSVTJ4WQkBAu8/efgn+t4QOaJ9aePXsiNjZWqvOfP3+Ovn37olu3bt+9RcapU6fg7u7eptdYvnw5evXqhfHjx8PY2JhLlMnNzZVqpRUREYEJEyZw///69SvOnTuHtLQ0jBw5EsbGxlBRUYGHhwfi4uKwc+dOHDhwADQaDYsWLeIWqHNQW1sLQ0NDuRZxFxUVgU6nIyUlhWeluX//fvTq1Qt6enpITU0Vuy5r8uTJWLVqFc82Th6PSqUiNDQUQUFB0NDQQNeuXREbG4vjx4+LXA03NDQgPj4eLBZLIMlJXkhMTMTo0aOhr6/Pt4p58+YNNDQ0ZG5nM2rUKGzYsEHo/rS0NEydOlXo/hs3bmDw4MHQ0tLC6tWrpSohqaurQ48ePTBv3jwAzc8m5/dYuHAhXFxcoKKiAj8/P2RnZ+PJkycSX6Mljh07BhqNhpSUFGhqauL333+XaTxB4ISIjY2NsXnzZh6nbePGjfD09BR6bnl5OXx8fGBvby82i1UYjI2N8eDBA6nOrampgZqamkzKSm2Bf7XhA4CKigqYmZkhKytLqvNbekWLFy+WS6NZcfDo0SMYGBi06TW+FaXmEGVCQkLAYDAkIsqcOnUK2traIllsFRUV+OOPP7BkyRL4+/tDU1MTnTp1wi+//IJp06bh0KFDPNc6cOAATE1NZSZaNDQ0IC4uDjo6Oq3mIy5fvswVAo6Li2uVxg00TzDBwcEA/i+PR6VSMX36dJ48XlNTE0pKSrBw4UK4urpCRUUFvr6+yMzMbNWwHDlyBJqamli8eHGbsI779euH8PBwoSo0S5cuxdChQ2W6xvz58zF37lyh+xcsWCBWPvfatWvw8/MDi8XCmjVrRDoPHHAUngIDA/Hq1Sts3LgRenp66Ny5M9f4nThxQuzxxMW1a9egpaWF+fPnQ09PT256lqdPn4aHhweMjIywceNGgVGKhoYGGBoa8q20CYJAfn4+aDQaFixYIJf5TEdHR+oyhMLCQnh5ecl8D/LGv97wAc2sPSaTKbK4szW8ePECAxorBT8AACAASURBVAYMgL29vchianng69ev6Ny5c5upwIsSpeYQZdLT00USZWpra2FqaipVLc/JkyehoaEBOp2OwYMHo0+fPlBTU4O+vj6GDx+O5ORkuLi4YMmSJVJ/1pcvX8LNzQ0DBgwQm/D07NkzTJs2DWQyGaNGjRIqSH3nzh0YGxvz5PHE8X4/fPiAgoIC/Prrr2AymTAyMsKkSZNQVFTE95uUl5ejd+/e6NOnj1RydMJQV1cHZWVl9OvXT2j969evX0U6C6KwadMmjBw5Uuj+6OhopKamij3elStX4Ovry82ltWawGhsbufWSHLFnW1tbaGtrS71KkQRPnjyBiYkJpkyZAlNTUyQkJEj9Tp89exZeXl4wMDBAXl6eSKO1fv169OvXj/v/27dvERgYCCsrK5ECD5KATqdLvWILCgpqE6lEWfFfYfiA5lwGlUqV6QcnCAJ5eXmgUqlYsGCBXOjerUFdXb3N6O3btm2Dr6+v2Mc3NDTgwoULAokyY8aMkSoXd/v2bW6B+sWLF8FgMPDu3Tuw2Wzcv38f+fn5mDJlCuzs7EAikWBmZoZff/0V2dnZuHr1qljf/+HDh8FgMJCYmChVDvPjx49ITk4Gi8WCl5cXDh06xDPO9evX0b59e5ibm0tNZCAIAqWlpUhKSoKnpyeUlZXh5eWF5ORk3Lp1CwRBoLGxEfPmzYOWlpZEBf2t4fTp0+jWrRtUVFRafc42b94MFxcXqSfsc+fOwdnZWej+sLAw5OXlSTzupUuX4OPjA11dXaxbt477PLx8+RLr16/H0KFDoaysjA4dOmDixIk4c+YMTp48CRqN9l31IN+9ewcnJyeEhITA3t4eEydOlOhZPH/+PPr27Qt9fX2sX79e7FVafX099PT0cOHCBRQWFkJTUxOzZs2S+8pWTU1NqpZEVVVVUFVVlYh9/73wX2P4gGb2mJaWlszqAH///Td8fX1hY2Mjl15rwmBpadlmuUVZRak5RJmxY8eiffv2UFZW5pJFxCHKvHz5Erq6ujykj9jYWKGEnri4OPj4+CAnJwfjxo2DtbU1FBUV4eLigsmTJ2PTpk24d+8e97qNjY2YM2cOWCyWxKxVQaivr0d+fj7s7OxgaWmJ1NRUhIeHg06nw9jYWK55yC9fvmD//v2YOHEiDAwMoKWlhXHjxmHHjh3YvXs3mEwm5s+fL3Poc+HChRg5cqRIfUQ2m41u3bpJXNzNAUeKThgGDx6MPXv2SDU2AJw5cwaOjo5QVVUFi8WChoYGgoODsWLFClAoFG6O9NWrV9DS0sKhQ4ekvpa0qKqqgo+PD7y9veHm5oaQkBCRBqykpATe3t7Q1dVFbm6uVI72qlWrwGQyYWJi0mblFV26dJGKeLR9+3Z4e3u3wR3Jjv8qwwcA6enpsLS0lLlpIkEQ2LRpE2g0GubOnSt3LwpozsG1VGGQF+QlSt3U1AQXFxfk5OTwKMqIIspwtFWTkpJ4ttfU1MDU1FRgM9yqqiqwWCyenEV1dTXOnDmDVatWYcSIETA0NISqqirc3Nygo6MDa2trXL9+Xa7h4traWkRGRqJjx45QVFREfHw8JkyYgMTERLldoyU4pSOrV6/GwIEDoaKiAkdHRxgYGMDe3h4vXryQeuxevXohODgYs2fPFnnsyZMnoa+vLxWxhCAIKCkpCc3/9u7dG3/++adEYz579gzZ2dncMhJnZ2eMGzcOTk5O0NfXR2ZmJszMzLiSeQ0NDdwIxY9CQ0MDwsLC4OTkhH79+sHX11egweCsZHV0dLB27VqpI0sHDx4Ek8mEsrJyq6xaWUAQBNq1aydVNCUgIECqlf73wH+d4QOacwqenp5yCVWWl5fDz88PXbt2lamWRRDCwsLahA0mL1Hq1atXC5UlE0aUyc/Ph7u7O6ZMmSLQIJ07dw5MJlNg6G379u2wtbVtdaWze/dukMlkeHp6wtfXF3Q6HQwGA35+fli8eDEOHz4sVfiYIAjs3bsXRkZG3Dze7du3MW7cOCgqKsLAwOC7dPyora3FsWPHMH36dNDpdLRr1w4eHh7YuHGjRPm/r1+/QklJCd26dRNbdcPf35/PWREX1tbWuHbtmsB9tra2IiMntbW1OHLkCKZNmwYzMzPQ6XSEhoZi27ZtfKGyU6dOgUKhQFVVFRs2bODm+Xx9fX94SzKCIBAfHw8TExP4+fmhV69eXBk8Tu5SW1sbWVlZUjvTnz9/xrhx46Cvr4+TJ09izZo18PPzk+fH4KKhoQEdOnSQ+LzPnz9DRUXlh3XkEIX/SsPX1NSEgIAAhIaGymU1QBAEtmzZAjqdjvj4eLmt/uLj42UidQjDpEmTZF6hvHjxAhQKRagsWUtwiDKpqanQ0tJChw4dYGNjgxkzZuDQoUN8ZI7o6GiEhIQIHKd3794CGbpNTU1YsGABmEwmTw6MIAiUlZWhsLAQM2fOhKenJ1RVVWFoaIjg4GCsWrUKZ8+ebVUmq7S0FJ6enrCyshKYx7tw4QJUVVVBo9EQEBCAs2fPthkp6Vvs2LED6urqMDMzg7q6Ouzs7DB79mycOnWqVcfu2LFjcHFxgbKystjP6/3790GhUMSSwvsWAQEBQgk0gnrxcVa6GRkZ8PHxgYqKCtzd3bF06VJcvXq1VQPG+Z1PnDgBDw8PMBgM0Ol0qe67rbB69WqwWCwEBQXB3Nwc3t7eYLFYyMzMlLq/HwAcP34cenp6iIqK4pbk1NbWQktLq03SMlVVVVBSUpL4vM2bN2PQoEFyvx954b/S8AHNHq+zs7NcZbFev36NgIAAWFpayqW1y5o1a/Dbb7/J4c7+DwRBQEdHRyZVGnFlyb5FbGws3N3d8fnzZ4FEmQULFuDs2bP4+PEjjIyMsH//fr4xSktLQaPReLz8N2/eoE+fPvDw8BArfMtms3H37l1s2rQJkyZNgrOzMxQVFWFtbY3w8HDk5OTg+vXr+Pvvv7m6mtnZ2UKL2wmCgLq6OrfXmrGxMZydnbFz587vIn7w9u1b9O/fH25ubtizZw/mzp0LR0dHqKmpYfDgwVi7di2ePXvGc058fDyGDRsmcY5l8uTJmDx5ssT3GBMTg+XLlwvcx+nFV11djaKiIkycOBGGhobQ0tJCeHg4du3aJXZqIj8/H4aGhtxVfWlpKdTU1ODg4AATExPk5+f/Y8Tok5OT0alTJ3Tp0oWnH6A0qK6uxqRJk6CtrS0wPZKens4jSScvfPjwARoaGhKf5+vri/z8fLnfj7zwX2v4gOYJw9DQUK5xZoIgsH37dtDpdMycOVMm723Pnj1Cle2lxbei1NJg586dsLS0lChUnJ6ezlegzsG3ijIqKipwcXGBqqoqzpw5w+fdT5kyBVFRUQCac08sFgvz5s2TaUKrr6/HlStXkJ2djdDQUDAYDJBIJDCZTERFRSE/Px8PHjwQutLo27cvt3N5U1MT9u7dCzc3N+jr6yM9PV3sgnhpwWazkZiYCAaDwb2Pt2/fYsuWLQgNDQWdTudRInFycoKfn5/EtWXv378HlUqVWNoqOzsbERERPNs4TZjbtWuHPn36QFlZGZ6enkhKSuKyWSXBpUuXQKPRuAXZHz9+hLGxMfLz83kUTszMzLB169YfZgBLS0sRGBgITU1NTJo0CTQaDaNHj4aenp5UJRZnz56FkZERQkNDhYYOv379Ck1NTbmLZ5eXl4PJZEp0TmVlJVRVVYX2uvwn4L/a8AHNrVHodDqOHTsm13HfvHmDYcOGwdzcXGo2VUlJidw7EosjSt0aKisrwWQyxW79BDQbShaLJTab9sOHD9i1axesrKygoqLCR5SprKwEnU7HhAkToKmpKTc9xJZ5PD8/P1y7dg2nTp1CSkoKgoKCoK+vD3V1dfTt2xfx8fHYu3cvV1g3Pj5eIHGipKQEQUFBoFAomDVrVpsL8Z49exY6OjqIjY3lYQ221J7s3r07SCQSunTpgtjYWNy9e1ciI5OcnCyxQ/bHH3/A09MTnz9/xp49exAZGQkdHR3o6OigY8eO2Ldvn0zOQXl5OVgsFjdKwGazMWjQIL7VaUtNSwsLC2zfvv275f04GqQMBgOrVq3iinCXlpaCxWIhODgYTCYTN27cEGu82tpaxMTEgMlkYt++fSKPX7lyJYKCgmT6DN/i6dOn0NfXl+ic33//vU1Wn/LEf73hA5rrmWg0WpuUDuzcuRMMBgMxMTESU35fvnwpsTclCtKIUrdEREQEJk6cKPbxnO9WmqL/qqoq6OvrIy8vj4coo6urCzKZjC5duog9SYhCyzwepxu3ILx9+xaHDh3CggULMHDgQFCpVDCZTDg7O8PU1BRHjx4V6HU/ffoUU6dOBZlMRmhoaJuKILx//x6+vr5wdXUV6GwcPHgQzs7OUFNTQ2RkJHR1daGrq4uoqCjs2bNHpPpObW0tlzghCgRB4MaNG4iNjUXnzp2hrKyM/v37Iy0tDffu3cPTp0+hq6sr7UcF0MwGdnJywrJly7jbFi9ejB49egiNShAEgT/++AOurq6wtLTEjh072swAtuw6kZKSIjCf/Pz5c5iZmWHw4MGgUqkiO3RcvnwZFhYWCAoKErsOrrq6GnQ6HXfu3JHqcwjCvXv3YGZmJtE5/fv3l0vH9rbE/4ThA5oLunV1dVtVkZcW7969w4gRI2BqaiqRAgaHMSWvPFFZWRkoFIrU43FkycQNUbQsUJcWJ06c4JFCO3PmDBgMBry8vKCmpgYFBYVWiTKi0LI/Xmt5PGEgCIJLrVdUVETv3r2hrKwMY2NjhISEIC0tDefPn+c6PZWVlVi+fDm0tLS45SptQYRhs9lISUkBnU7nWw3MmDED/v7+XAIRQRC4e/cuUlNT0b9/f24z4mXLluHatWsCDcL27dvh4OAgcF9FRQUKCgowduxYaGpqwsTEBJMmTUKHDh34nIIbN27AxsZG6s9JEARGjRqFESNGcL/H4uJiaGlpifUuEwSBw4cPw9nZGV27dsWuXbvkZgDv3r2LESNGgE6nIykpSeSz+eHDB7i6uqJPnz6gUCgCm7vW19cjISEBdDpdKuOxYsUKgcQxaSHp7/fu3Tuoqqp+l56LsuB/xvABzYK9dnZ2bZaP4agnTJs2TexeY5qamnILj2VmZkrcOJUDjiyZOCEVoLnI/9sCdWkxfvx4jBs3DklJSaDT6dwc1qVLl6CpqYmjR48KJMqcOXNGqMdfV1eH5ORkUCgUzJgxQy51nQwGAy9evEBTUxNu376NDRs2YMKECXB0dISCggLs7OwQGRmJ3NxcXLlyBXl5ebC2tkbXrl2Rl5fXJrWgFy9ehJ6eHqKjo7nfhb29PTw8PIQKR3/9+hWHDx9GdHQ0t3Rg9OjR2LJlC5cZSRAEXFxcsGnTJrDZbFy+fBmLFi1C9+7doaKigkGDBmHNmjU8CimGhoZ8uUGO0LK0SEpKgoODA/d9evLkCeh0usR1awRB4NChQ3B0dISNjQ12794ttQG8d+8eRo4cCRqNhuXLl0vkjH39+hV+fn5wcXEBlUrlMW43b96Era0tBg0aJHUN7pcvX0Cj0aRqPyQIJSUlcHJyEvv4nJwcuXedaQv8Txk+giAQGRmJAQMGtBkb7/379wgJCYGxsbFYIUcHBwdcvnxZLtf+VpRaEiQkJIgtViysQF1aPHv2DF26dIGFhQXKysp49o0bN46ndU5LooyDgwNUVFTg4+PDVZRpamrCnj17YGhoCD8/P7nqNfr6+gpVIKmrq8OlS5ewZs0ajBkzBhYWFlBSUoKbmxsCAwNhY2MDGo2GpUuXyqUHXktUVFTA398fjo6OuHr1KlRUVCRq/Pn06VOsXbsWgwcPhqqqKhwdHTF9+nSMHTsWioqKoFKpsLS0xIwZM3Ds2DGhhK5+/frxqaZ824tPEhw8eBBaWlrcIv6vX7/Czs4O6enpUo0HNM8BBw4cgIODA+zs7LB3716xV+QPHjzAqFGjQKVSsWzZMqkd6MbGRkRERMDKygoMBgPZ2dlYunQpqFQqNmzYIHOEYOnSpVI7wN/i9OnTEnWR8fT0lHoO+p74nzJ8QHN40dvbG1FRUW1ai7Vv3z5oaWlhypQprS77Bw0aJJX487cQJUrdGm7dugUajSaWl1lXVwdPT09MnjxZLt8fZ8UydOhQ6Ojo8IVZ3759CyqVKjRvwSHK/Pbbb1wihaqqKqZNmyZz65lvsXDhQsTHx4t9/OfPn/Hnn39ixYoVGDp0KJhMJjp16oQOHTqgW7duyMnJkVldhwOCIJCeng5VVVWYmprCwsJCovMbGxtx7tw5xMfHw8zMDJ07d4aamhrat28PExMT/Oc//xGpIvPbb79h9erVPNuE9eIThbt374JGo3GJYwRBYMyYMQgJCZFbbe6+fftgZ2cHBwcHHDhwQOi4jx49wpgxY0ClUrFkyRK5sBUJgsD8+fOhpaWFjh07wsTERCaVnpb49OkTqFSqzO2mgGYxjD59+oh17OvXr6GmpibXxsJthf85wwc0hwNsbW2xYsWKNr1ORUUFQkNDYWBgIFSyafz48VK3VGoJSUWpOeDIkomj68lmszFy5EgMGTJEZqo4QRBITU3lyVGFh4dj/PjxfMdmZGSgT58+Qiemt2/fIjIyEnQ6HUuWLEFubi6PokxERAS2b98uc9PXgwcPom/fvjKN8ebNG2zcuBFubm7o2LEjOnXqBBqNhsDAQCQmJuL48eMiySetISgoiJsXFVVqU15ejry8PAQFBYFMJsPW1pZbHM9hjF68eBFKSkoICAgAhUKBlZUVYmJiBK78UlJSEB0dzbNNVC8+QaioqICxsTE2btzI3ZadnQ1ra2u5544IgsCePXtgY2MDR0dHHDx4kPucPX78GGPHjgWFQsHChQtl+l2+RVNTE1auXAklJSWoqKhAX18fs2bNkpszvnDhQowbN07mcYqKijBw4ECxjs3MzMSoUaNkvub3wP+k4QOac1Q6OjpSC/NKgqKiIrBYLEycOJFvRbZo0SIkJCTIfA1pRalbkyX7FrGxsXBzc5PZo6usrERAQACcnJx4FD0+ffoEbW1tPrJMY2Mjl5jQEqLyeC1bL/n5+UFVVVUmosybN2+grq4ut8mpuroaq1evho6ODoyNjeHn5wd3d3coKyvD1NQUo0ePRkZGBi5evCh2vailpSXs7OzQo0cP2Nvb83j9LTvI29jYgEwmY/jw4diwYUOrRJHp06cjKioKTU1NuHTpEk+ub+DAgVi9ejUePnyI3bt386l1iNuLj4PGxkb07duXpyTnwoULoNFoclnBCAObzUZhYSG6du0KW1tb9O/fHxQKBfPnz5c5P/wtHj9+DHd3d/Ts2ROPHz/Gnj17QKVSYWJigvHjx8ul/rCyshIUCkWqhtMtUVhYKHZpgru7Ow4cOCDT9b4X/mcNH/B/KiFtJfDaEpWVlRg7diz09fV5Jvb169dj7NixMo0trSi1JLJk6enpMDc3lzk/deXKFRgYGGDKlCkCyR6HDh2Cvr4+n1E6efIkdHV18fXrV66XbmhoCH9/f7HzeMJaL4kiyrSEjo6O3CfgpqYmFBYWonv37jA0NERaWhpKSkrw+++/Y/z48XBwcICCggIcHBwwfvx4rF+/Hrdu3eKbIF+/fg11dXUoKSnh8+fPWLNmDchkMsLDwxEQEAA1NTU4OTlh3rx5OH/+vNh57oqKCp7C8Zbbd+7ciXHjxkFLSwssFgtkMhkHDhzg/n6S9uKbOnUqvL29uff25s0baGtrf5cJ9dmzZwgPD4eysjKoVCq6deuGI0eOyM3RYbPZyMrKAoVCQWpqKo+zefbsWdBoNFhYWGDEiBFy0RmeO3cuVwhCWmzdurXVXoscvHz5EmQyuU0IXG2B/2nDBzQX3jIYDLmxoEShuLgY2traGD9+PD5//ozi4mL0799fpjGlEaUmCAKDBg3C4sWLRR67a9cuiQrUhV0vMzMTNBqNb+X2LcLCwjBp0iS+7SNGjEBkZCQ8PT3RtWvXVuvxxIEoooygVfCQIUPaNEpw/vx5DBkyBFQqFfHx8VxnpqamBhcvXkRGRgZGjx4NMzMzblnCjBkzUFBQgPT0dC5tf/r06bCwsACZTIaKigo8PT35iEOSIC0tDQMGDBC6nyAIlJSUoEOHDvDy8uKqtHTr1g2LFi0Sy3j85z//gampKXeF1djYiN69e7fa3V0eKCsrQ1RUFDQ0NDBnzhx8+PABbDYbBQUFsLCwQPfu3XH06FGZDGBZWRn69u0LZ2dnoY7m7du3oa2tDUtLS/j4+IjNDBcGjtyYLL97Xl6eWI55amqqzA7898T/vOEDmpUGDA0NZc4BiYtPnz4hPDwcurq6yM7OhpWVlUzjSSNKvWPHDrFkyTgF6rIUkn/69AlBQUGws7MTa7VUWVkJLS0tbp81oDmPFxISgnbt2mHJkiVtwsptSZT5tvUShyiTmJgokzKOuHj8+DEmT54MdXV1jB07VqD4wsePH3H8+HHExMTAxsYG7du35yq29O7dG6mpqXj16hU+f/6MESNGwMbGRmoHr76+HsbGxiJVdBgMBl6+fImqqioUFRXBwMAADAYDTCYTv/76K3bs2CEwasBZ8bS8vxkzZsDb27vNpMdevHiB3377DRoaGpg9e7bAQvGmpiZs27YNZmZmcHNzw/HjxyUygARB4PfffweVSkViYqLI5/bFixewsLCAubk53NzcZA6zzpo1SyJBim+xdu1agXn3b+Hi4tImLdbaCj8N3//H3Llz4eLiIrOXJQmOHDkCbW1tdOrUSerEOUeUWhK1BnFlyTgF6rLIvd24cQPGxsaYMGGCRLqm+/fvh5GRESoqKnjyePPmzZO7vqkwlJWVIS8vj4co4+PjA3Nz8+/mJFVUVGDZsmVgMpno378/jh49iurqahw8eBCTJ0+GsbEx16hwVG+SkpKQkJCA/v37g0wmQ1dXF0OHDkVgYCBUVVWRm5sr1b3s3r0b1tbWrRqiHj168DgsnF58jx49QmZmJnx9faGiogJXV1csXLgQJSUlePr0KZhMJs/EWVBQAAMDA7mXfgDNYbmJEyeCTCZj5syZYnV1aGpqwpYtW2BqaoqePXuKpWrz6tUr+Pr6ws7OTiINzcrKSvTs2RMmJiawsbGR6Vl7+/atRKUt3yI9PV0kOenZs2egUqlid47/J+Cn4fv/IAgCo0ePRmBg4HcVt/306RN++eUXaGtrC1RyEAVpRKnDw8NFeoGcAnVpFdYJgkBOTg6oVKpUoUGCINCzZ0+oqanx5PHq6upgbGws1XclCwiCwO3bt5GYmIj27dtziTLTp0+Xiigj6bVv3ryJ4OBgKCkp4ZdffoGZmRmWLVuGmzdvclszUSgUqKmp8awqCILAo0ePsHXrVkybNg12dnZo164d1NXVERISgszMTFy6dEms3AxBEHB3d8f69euFHhMaGsrTY1JQL766ujocP34csbGxsLS0RPv27WFnZ4cNGzbg1atXuH37NqhUqtzb7JSXl2Py5Mkgk8mIiYmRyqA0NjZi8+bNMDY2hoeHh8BaXYIgsG3bNtDpdMybN0+qfF1NTQ0CAwNhYGAAIyMjmcKVMTExEjNrOUhKSkJcXJzIYyIjI6Ua/0fhp+Frgbq6Onh4ePAUTH8P6OvrY9OmTdDT08Ovv/4qUXhDUlHqkydPipQl4xSoS1vu8eXLF4wcORLW1tZShdZu3LgBDw8PWFhYQENDg08G7uDBgzAxMflhiXRjY2OUlpbiwoULWLJkCZco4+bmJhFRpjV8+fIFe/fuxfjx46GnpwcdHR2u1ubu3bvRr18/aGlpYfny5aisrMTGjRvh4uKCgIAAkWN//PgRvr6+YDKZGDZsGOzs7KCgoABHR0dMmDABeXl5uH37tkAH8NKlS2AymUIN/cKFCzFnzhzu/4J68XFAEASGDRuGYcOGYf369QgKCoK6ujo6d+6MgQMH4uTJk3Ihebx69Yqrozp9+nSJGvoKQ2NjIzZu3AgjIyN4eXlxtTffvXuHYcOGwcLCQubG1U1NTZgwYQJYLBZYLJZYJDRBeP36NchkslQ1o4sXLxaZY3VwcJBJtvBH4Kfh+waVlZWwsLDgK8RtS/To0QNnzpzBly9fMHHiRLBYLK5slyhIIkpdU1MDExOTVmXJZC1Qv3XrFszMzBARESFx2cObN28QGRkJBoOBtWvXorGxEbt374apqSnfWIMGDRLa/62tERwczFNjBjSrivzxxx98RJmVK1cKJcq0BEEQKC0txYoVK+Dh4QFlZWX069cPq1atwp07dwT+Fjdv3sSYMWNAJpNhbm4Oe3t7sWtCW+ae8vLyUF1djfPnzyMtLQ0hISEwMTGBiooKevfujdjYWOzcuRPPnj0DQRAYOXKk0BKF/Px8jBgxgvs/pxefICxatAiurq7cEDibzcbgwYMRGBiIefPmwcnJCaqqqvD390d2drbE1PzXr19j2rRpIJPJiI6OlptYQEs0NDQgLy8PBgYGsLGxAYVCQVxcnEztylqCIAiuqguVShXa5V4UoqOjpcpNJyQktNos+9GjR6DT6d+lL6U88dPwCcCzZ8+gpaUltm6lrBg2bBhPOPDPP/+EgYEBQkNDW81xPH/+XCJR6jlz5rQqS8YpUJcm3NtyIt28ebNE59bV1SEpKUloPd7w4cMRGxvLs+3Ro0fQ0NBo8zZAgrBq1SqRzVpbEmVMTExApVIxfPhwHqJMZWUlTzmAkZERJk+ejIMHD0pUqP3y5UuoqKiARCLB29sbFy9eFPvc27dvw9LSEqGhoXyruMrKShw9ehRLly7F4MGDwWQyQaPR4OnpiS5dumDTpk18+bELFy7A0dERQPPz9Msvvwh8lnbv3g1tbW0eY5SYmAgXFxeelfz79++xbds2jBkzBgwGA6amppg6dSoOHTokNB//5s0bzJgxA2QyGVOmTGkTYfqWqKysREhICOh0OhgMBvr37y/RbyAO1q9fD3V1dairq0vVLlVHxgAAIABJREFUfaW8vBxkMlni8G5sbCySk5OF7l+6dKlM5JkfhZ+GTwiuXLkCGo0ml07rohAdHY1Vq1bxbKuqqsLkyZOhpaUlsFM5IJkodWlpKahUaqteb1xcnFQF6tXV1RgzZgwsLS0lItmIW4/37t07MBgMvskkISFBrBojeeP06dMSl4+UlZVh/fr18Pb2hpKSEjp37oyOHTvCzs4Oy5Ytk6k28NGjR2AwGNDR0UF6ejr09fW53drFcWCqq6vx66+/wtzcXGTrrr///ht79+6Fq6srtLS0oKamBn19fQQFBSE5ORl79+6Furo6gOaQqqqqKt8YN2/eBJVK5QkFHj16FEwmEy9fvhR6bTabjevXryMxMZHbJaPlqvjt27eIjY0FmUzGpEmTvotTdPjwYWhra2Py5Mmorq5GfX091q1bB11dXQwYMECu80dRURHU1NSgqqoqdkSoJSZNmoSZM2dKdM6UKVOQkZEhdL+1tbVMbdB+FH4avlZw4MABMJlMmdUPRCEpKQkxMTEC9506dQpGRkYYNWoUPnz4wLNPXFHqpqYmODs7t6rskpGRIVWB+p07d2BpaYkxY8ZItErh5PG6du0qFmt0x44dMDc35wkhVVdXQ0dHh4dF+D1QVVUFRUVFsVhs79+/x9atWzF69GjQaDSYm5tj2rRpWLduHVJSUngUZaQlyqxbtw6Ojo7cDuiNjY3YuXMnnJ2dYWxsjKysLLHYyps3bwaVSkVubq7IMPenT5/AYDBw7do1PHjwAPn5+Zg6dSq3Ca65uTmGDRsGMpmMK1eucHN17969g76+PrZt28Yd6/nz52AwGGIxJVvi8+fP2Lt3L8aMGQNVVVX88ssvsLCwQE5OjtzVVgRdOyIiAnp6ejhx4gTf/vr6eqxduxY6OjoYOHCgzPk+Di5evAgNDQ2oqKjwfIfi4MWLF9DQ0BC7vx8AREVFIScnR+C+u3fvQktL67s1+pUnfho+EcjMzIS5ubnQPIU8sGXLFgQHBwvdX11djejoaDCZTK6hk0SUOiMjo1VZMmkL1DkTZV5entjnCMrjiQOCIDBkyBDMnj2bZ/uOHTtgbW393XMMlpaWAlmHTU1NuHDhAubPn8/NUQ0ePBg5OTl49uyZwLEaGxtlIsoEBwfDxsaGr38bQRA4e/YsAgICQKPRkJCQIJLYce/ePVhbWyM4OFikGHNWVpZADVUbGxts2bIFCQkJIJPJsLGxgaKiIpycnKClpQU/Pz/cvXsXbDYbtbW16NatG1auXNnqtQThw4cPiI+Ph4aGBqKionDixAluob2ysjLc3d2xdOlSXL16Va6T859//gl9fX1ERESI/I7q6uqQlZUFbW1tDBo0CFevXpX5+vfu3YOWlhZUVFQk1vkdP348D/lIFMLCwoS2t1qwYAGfNuu/BT8NnxiYMWMGevfu3WYswj///FOsnmVnz56FiYkJRowYgZycHLFEqTk0d2GMsDNnzkhcoF5TU4Pw8HCYmZmJ3dW+ZR4vJiZGKo/8zZs3oNPpPG2cCIKAp6cnMjMzJR5PFoSFhXHr4V6/fo0NGzZgxIgR0NDQgI2NDWbOnCk1K7E1osyNGzd4JnGCIECn06GkpNSqJ//w4UNMnDgR6urqGDduHG7fvi302JqaGkRFRcHExKTVkoKGhgaYmZnxhd2GDBmCgoICnl58VVVV8Pf3h6WlJUaMGAFDQ0OoqqqCyWTCzMwMu3btQllZmViEqoqKCiQkJEBDQwORkZECHbaamhocOXIE06ZNg7m5OWg0GkaNGoX8/Hyp6+K+fv2KKVOmgMViSVxOU1tbi8zMTLBYLPj7+8tcqlFeXg5zc3OoqqpiyZIlYhPRnj17Bg0NDbEjO8HBwQJXlgRBwNzcnNs949+Gn4ZPDLDZbAwdOhQhISFtsqy/f/8+jIyMxDr269eviImJQZcuXUQqKhAEAV9fX6GyZHfu3JG4QP3+/fuwtrZGSEiIWP3Ivs3jPXz4UOxrCcKWLVtgZWXF44Rw6r7EKUSWBxoaGhAdHQ1bW1vY2dlBXV0dw4YNw++//94meSVhRJl169bh8OHDYDKZcHBwEGus9+/fY8mSJWAwGPDx8WlViWT79u2gUqnIysoSesyBAwdgYWHBs+KOi4vDsmXLeHrxZWVlwcrKimeFtGrVKujq6mLu3Lnw8/MDg8EAnU7HoEGDsGjRIhw+fJgnvF9ZWYl58+ZBQ0MD4eHhEqUgnj9/jnXr1iEwMBBqamro1q0bEhIScPbsWbGiBefPn4eJiQlGjRolU1F9bW0tMjIyoKWlhYCAANy8eVPqsT59+oTu3btz23CJa/zCw8PFFg4PCAgQmE4pLS2Frq5um7Z2a0v8NHxioqamBq6urhKFCcTFly9foKCgIPZDVF9fD2VlZRgZGSEoKEioB1tQUAArKyuBqw5pCtS3bdsGKpWKnJwcse5V0jyeOCAIAv7+/ny1RdHR0dwcV1vgxYsXyM3NxZAhQ6Curg5zc3MwGAycO3fuu4dZWyrKqKiooGPHjrCxsZGo9VJtbS3Wr1/P7eawefNmgc/Jw4cPYWdnh2HDhglUF+KsuLOzs7nbcnJyMG7cOG4vvhMnToDBYPB0a7906RKoVCpPnSdBEHjx4gV2796NWbNmwcvLC6qqqtDX14eVlRUUFRXh4+PDJ5YtKRoaGnD69GnEx8fD3t4e6urqGDJkCHJzc/kKxWtraxEXFwdNTU2hTYilQU1NDdLS0qCpqYkhQ4aIHTn5FnV1dRg8eDBUVFQwevRoschMjx8/BoVCESvq4uPjI5BIM2fOHD6m9b8JPw2fBHj37h2MjIzwn//8R+5jq6ioiB3+44hS19TUIC4uDgwGAwUFBTzGqKKiApqamgJDEZ8+fYKNjY3YBeq1tbVc/UpxQjRv3rxBRESExHk8cfHq1SvQaDSee/n48SM0NTXl1s2eoy4SExMDKysrUKlUhISEYPPmzXj79i1qa2uhoKAgt3otaREYGAhdXV1MnDgRfn5+UFNTk4gow2azUVxcDC8vL7BYLCQlJfE9h7W1tZg4cSIMDQ0FkjSuX78OBoPBXc0dO3YMvXv3RlpaGsLCwkCn03kIIO/evYOurq5IQ/Lp0ycsWLAA6urqcHd3R2hoKJydnaGoqAhra2uMGzcOOTk5uHbtmkxyWW/evMHmzZsREhLC021+zZo1sLCwwNChQ9ssmvD161esWrUKmpqaGDZsmFRGnc1mY8KECVBWVoavr69YKZmwsDCxBOq9vLz4nFaCIGBkZCQ3ws6PwE/DJyEePHgABoOBI0eOyHVcc3PzVvMuLfGtKHVJSQksLCwQGBjIJS+MGzdOYIcDToH6pEmTxFq1PXr0CPb29ggKChIrkS9rHk9cbNy4Eba2tjyrlLy8PDg7O0sdjn7y5AmysrIwaNAgrp7kokWLcOnSJYGetL29PUpKSqT+DLKCzWZDXV0dioqKXAPckijj4eEhEVHm+vXrGD16NMhkMqZNm8ZHxtm1axdoNBrS09P5np2wsDDEx8fjfVUdlu25DJ3h89B99iawhs5BaOJmfKiq496fl5cXH0mpJT5//owlS5aASqVi9OjRfGUu9fX1uHr1KrKzs/Hrr79yV4Ourq6YMmUK8vPzcf/+fameg6amJpw/fx4eHh7o2LEjunTpggEDBiAjIwMPHjxos9BedXU1UlJSwGAwMGLECInKgoD/K3RXUFBAjx49RDKsHzx4ACqVKvKddnNz42vbdvXqVRgaGv5rw5zAT8MnFc6dOwcajSZTfP5beHl5idVmR5godW1tLeLj40Gn05GQkAAWi8X3UEtaoF5YWAgajYY1a9a0+pATBIHdu3fLLY8nDgiCwMCBA7Fw4ULuNjabDRcXF7FZpjU1NSguLsbUqVNhYmICBoOBsLAwFBQU8JWOCEJUVNR3J9W0xPXr18FisVpta8UhysycOVMkUYaDly9fIi4uDhoaGhg+fDhPLdqTJ0/g6OiIgIAAHqbz0asPoDViIUwSDsF0bjH0Zh/k/pnNLYbp3GJE5V9B+MzF6Nu3r8Dn78uXL0hMTASNRkNISIhEcndVVVU4ffo0UlJSMHz4cOjr60NNTQ19+vTB7NmzsWfPHrx8+VLkZH3r1i3Y29tj4MCBKC8vR2VlJXbt2oXw8HCwWCwYGBhgwoQJ2Ldvn1g5bklRVVWFpKQk0Ol0jBw5UmKZsry8PHTp0gVdu3YVyUQfNWqUyK4ujo6OfLWIcXFxiI+Pl+i+/mn4afikxI4dO6Ctrd1qwa0kCA0NFUobbglRotRnzpxBp06d4OzszFesLm6Bel1dHaZMmQIDAwOR4Yy2yOOJi5cvX4JKpfIo31+5cgUMBkPgapMgCNy/fx9paWnw9vaGsrIyevXqhcTERFy/fl3iFUJubi7CwsJk/RhSY+XKlbCyskJKSorY53z48AGFhYUCiTIcRRkOvnz5grS0NOjp6aFnz57Yt28f2Gw26urqEB0dDX19fZSUlCD/4jOYzzsMvdlFPAbv2z/92UXQi92Ntcd4IxtVVVVYsWIF6HQ6goODcffuXbl8P+/evUNxcTEWLlwIX19f0Gg0MJlM+Pv7Y8mSJfjjjz+4RJXGxkYkJiaCSqXi999/F/h+EQSBv/76CytXrkTfvn2hrKwMDw8PrFixgisWLi9UVVVh+fLlXDaquM2WgeZmzgoKCtDT02u1fOXu3bug0+mthsOtra153i+CIKCnpydXp/9H4KfhkwFJSUmwsbERGS4QB7NmzcKyZctEHidKlHrOnDkIDAzE3LlzQaPRsHnzZhAEwS1QF7WSefr0KZycnBAQENBqqLJlHi8nJ+eHafWtX78eDg4OPDmeiIgIbn1RVVUV9u/fjwkTJkBfXx/a2tqIiIjA7t27pW4FxcGNGzdgaWkp0xiyYODAgdDU1JSpVyKHKDNq1CgwGAzo6+sjPDychyjT2NiIgoICODo6wtTUFGvXrsXXr1+xd+9eMHsOh9HsA60avG//zOcVI//iM1RXVyM5ORl0Oh3Dhw8XO9QvLQiCwPPnz7Fz507ExcXBw8MDKioq0NPTA4VCgYmJCQoLC8VuTfZteyhNTU2MHTsW27dvFytiIA4+f/7M1eoMDQ0VO5py6dIlKCsrg0ajCa0fBZqbO7cmSWZqasqz8r548SLMzMz+1WFO4KfhkwkEQeC3335D//79Ze5FlZGRITAn9y1aE6UuLS0FjUbjrvSuXbsGGxsbODg4QFNTs9UXAAD27dsHGo2GtLQ0oQ/298zjiQOCINC/f38sXbqU+/+pU6egpKQEFxcXKCsro0+fPkhJScHt27fl+sI2NDRAUVGxTVsStXZtFRUVUCgUuZXYcFovZWRk8BFlDh48iM+fP+P06dPw9/cHjUbDhIQVMEkQbNxogXPQSdME7Tp0QrvOiuisbQntaQXc/UazD0DT0llqQoc8wGazsWrVKqipqWH06NGYMGECHB0doaioCFtbW0RERCA3Nxc3btwQ6/1+/PgxsrKyuGo8Li4uWLBgAS5evChzq7NPnz5h8eLFoFKpCAsL42HICsPDhw9BoVCgqqoq1Kn466+/wGAwhBp7PT09nnlj2rRpYpdC/JPx0/DJiMbGRvj6+iI8PFymSbWwsFBkS5nnz5+DSqUKXF1xZMm+bTJ64sQJKCoqgkwmIy8vT+A9NjQ0YMaMGdDT0xMqrtsyjzd48ODvkscTF7du3YKKigqGDBnCzcP07NkTXbt2bZM8TEu4urr+EK3CixcvQltbu021ShsbG3Hx4kU+osz8+fOxZcsWOE7Phe5M/tUe1T8OJBIJpPYdoWjRE8o2/dGRpg/WpI3/d9ysAwhewy/19b3w5MkT9OrVC25ubnw6qXV1dbh8+TLWrFmDsLAwWFhYQElJCT169EB0dDS2bt2Khw8ftvq+19XV4cSJE4iLi4O1tTU3X5qXlyeTaPbHjx+xcOFCUCgU/Prrr3zh6W/x+vVr6OnpQUFBQei7PXToUKSmpgrcp6mpyXWk2Ww2WCyWxMSbfyJ+Gj45oKqqCvb29txVhzS4cOECnJ2dWz0mMzNTaE4pIyMDvXr14vH+OQXqR48exY0bN2BnZ4cBAwbgxYsX3GPKysrg6uqKQYMGCS3MbZnH+yf03WKz2bh27RqWLVsGd3d3KCsrw8rKCrq6utwWPo2NjbCxscGOHTva9F4mT57MJzD+PbBs2TKYmJhIJBcnK1oSZexce0I3dg+f0dOdVYT2qjSQSCQwRia2GvI0nVvMZXt+LxAEgbVr14JKpWLlypVir8Q+f/6MkydPIikpCcOGDYOuri7IZDL69euHOXPmYN++fa0atL///ht5eXkYPnw4V8Zt5syZ+PPPP6VS9/n48SPmz58PCoWC8PDwVqM5X758ga2tLTp16iSQjX7jxg0wmUyBuX8ymcydF86cOYOuXbtKfK//RPw0fHJCeXk5dHV1sWXLFqnOLysrA4vFavUYYaLUZWVlfMXAnAL1li2CGhoauOGS9evXo6ioCAwGA8nJyQLDZf+UPB7QTMpo2Z7GzMwM0dHROHz4MGpqakAQBLy8vJCUlMQ95/Tp09DW1pZIPFtSbNq0qVWd1bZCnz59oKKiIjdylaRYe+oxTBMO8Rkzrah1IJFIaNehM7oYdkO7jl3QQZ0JjX6/8R1rNrcYOadFh+zkhRcvXqB///5wcnKSC4HmzZs3KCoqwvz58+Hj4wMKhQIWi4WAgAAsW7YMx44dE5gK4JScLFiwAC4uLlBVVYWfnx+ysrJEruC+RUVFBebOnQsKhSJUvg1oLgHp06cPOnToIHCOGjx4sMAepIqKitz3Z9KkSa325vs34afhkyP++usv0Gg0qboF1NfXo0OHDkI9UGGi1BxZspYPJKdAXVij1mvXroHBYKBLly4oLCzk219bW4sVK1b80DxeU1MTSkpKeCYHTkNSYZPD06dP+XRJR44c2SZqOxzcuXMHxsbGbTa+INTV1UFRUREmJibf9botEV1wXeAqjjE6pTnMSSKhg4Y2lKz7ol2HTiCRSKANSeA7fsKmkjZX9ycIAhs3bgSVSsXSpUvbzIEjCAJPnz5FQUEBYmJi0LNnTygrK8PU1BSjRo1CRkYGLly4wLey+vDhA7Zv346wsDAwGAyYmJhgypQpOHTokNhO24cPHzBnzhxoaGhg/PjxfAo0QHOkJCQkBO3bt0daWhrPvqtXr4LFYvEJMrRv3x6NjY1oamoCg8H4R6U4ZEE7ACD9hNxw4sQJUkhICOnUqVMkCwsLic6l0+mkW7dukTQ1Nfn2bd++nbR161bSwYMHebbv2LGDtGTJEtL169dJnTp1IjU0NJB8fHxIFhYWpMzMTFK7du14ji8vLycFBweTFBQUSE5OTqTc3FzS0qVLSVFRUSQSiUTau3cvKS4ujmRtbU1KSUkhmZiYSPgNSI+3b9+S/vjjD9KRI0dIR48eJTGZTNKAAQNIPj4+JDc3N1Lnzp1FjpGVlUXasmUL6dy5c6T27duTysvLSba2tqSSkhKSsbGx3O+ZzWaTyGQyqaysjEQmk+U+viCcPn2aNHr0aFJgYCBp9erVbXKNxsZG0qtXr0jl5eWkv//+m+evvLyc9LfhIFI7bRv+8yrLSa9yx5NIJBJJMyyV1JlpSqo4upZUff0QScm6L4nqO433+LLrpHe7FpOoVCqJTqfz/DEYDL5tdDqdpKioKPbnePPmDSkqKopUVlZG2rRpE8nOzk62L0ZCsNls0r1790iXL18mXblyhXT58mXSvXv3SObm5iQnJyeSs7MzycnJiWRpaUnq0KEDiSAI0q1bt7jvwdWrV0murq6kAQMG/L/2zjyu5uz/4682JVqobisSpgyjhEGkbKUsFWZspZIaEmaYNGKoMfZ9GzQUYjJjUigthBRCI/uWNUX7vtzq3vv+/eHr/qTkVrcF5/l4eFx97jnvc+6te1+f9/u8z/tg1KhR+Prrr6t9pt8lOzsbGzduhJ+fHyZNmgRvb2/o6OhUabNo0SJs2rQJnp6eWL16tfD6mDFjMHr0aHznMAP//peK+68LcCT4OKZMtIVMSSZO71mBG1fiG+29akqY8DUCBw4cgK+vLy5fvgx1dXWR+/Xu3Rt79+5Fnz59qj03ZcoUDBs2DK6ursJrubm56NGjB44dO4aBAwdCIBDAwcEBZWVlOHr0KKSkpKrYiIqKgpOTE+bOnYtffvkFkpKSuHv3LpydnSEhIQEJCQmUlJRgy5YtGD58eP3fABHh8XhISEhAREQEIiMj8fTpUwwfPlz4IX//AysKAoEAw4YNw7hx47BgwQIAwNq1axEXF1ftpkFcmJmZ4ddff8WIESMaxf77+Pj4ICAgANu3b8e4cePq3L+0tBRpaWkfFrXUVOTk5EBdXR06OjpV/mlra0NHRwf7HwJnHhdUs038SrzcNg1UXvr/whf1B4qTTkGhz1i0H/lDlfZ2RtpYa/c1srOzkZmZKfyXkZFR5ed3r8nIyIgkkpcuXcKyZcswc+ZMLFu2DK1atar3ey5OuFwubty4gWvXrgnFMC0tDUZGRlXEUE9PD8XFxTh79iwiIyMRGRkJHo8HS0tLjBo1CiNGjICysnKNY2RlZWH9+vXYu3cvpk6disWLF0NbW1v4/NatW7Fw4UI4Ojpi7969kJCQwOHIeHgHnoesXh9IACjnCYTtJYkHCQlJjOihCXezrjDsUPO4nwpM+BoJHx8fhIeH4/z582jTpo1IfUaPHo1Zs2Zh7NixVa5XVFRAXV0d9+7dg6ampvC6i4sLWrdujR07dgB4cyd38eJFnDlzBq1btxa24/P58PHxgb+/Pw4fPgxzc3PhcxkZGfD29sY///wDIsKaNWvg7u4OSUnJBrz6D5OamoqoqChEREQgJiYGnTt3hpWVFUaNGoUBAwZARkamwWM8fvwYAwYMwOXLl9GtWzeUl5ejV69e2LhxI8aMGSOGV1GVn3/+GSoqKli8eLHYbdfE4MGDkZiYiMzMTCgqKgqvExEKCwurCNj7gpaamoqSkhKhgNUkajo6OlBXV6924/QumyPvYGtMMiBdXUzy4w6j4GIQpFV0IKtlgNL7F0B8HjQc1kNWS1/YTk5aEj+N/Ao/DOki8msnIhQVFdUqkqmpqbh9+zZKS0sBACoqKiJ5kurq6iJ/VsVNQUEBEhMTq4hhaWkp+vXrJxTDvn37oqioSCiC8fHx6NWrl/BG0djYuNrnNjMzE+vWrYO/vz8cHBzwyy+/CL9D/v77b0ybNg1WVlb4znsbVkc8RFlFJSDx4c++hAQgJy2FJdYGsB+g25hvSaPChK+RICI4OzsjLy8Px44dq/VL5C1ubm4wNjbGrFmzqlw/ffo0fv31VyQkJAivnTt3DtOnT8fdu3ehqKiIbdu24Y8//sDFixehoqIibPf69WtMnToVUlJSOHz4sNAD5XK52Lp1K9avXw9nZ2csWbIEr1+/hrOzM1q3bo19+/ZBT0+vwe9DRUUF4uPjERkZiYiICLx69QoWFhawsrKChYVFjWFdcbBlyxYEBwcjNjYWkpKSiIyMhIeHB+7cuQM5OTmxjnXkyBH8888/OHbsmFjtvgsRITs7G48fP4a5uTm0tbUxderUaqIGoFZB09HRgYqKSq3hso/B4/EwyvY7PO3pDIFE9b9rEvCRfyEQJbdjIKgohYxKRyibTkXrLv2qtJOVlsQlr2FQafvxELaonDhxArNmzcLUqVOxYsUKyMjICL3J2rzIt/+XlJQUWSRVVFQgLS0ttrm/z+vXr4VC+FYM27ZtKxRDQ0NDcLlcxMXFISoqCllZWbCwsIClpSUsLCyqRJvS09Oxbt06HDhwANOnT4eXlxc0NDQQGxsLm4UboDxsBiAlukfcWkYSS6y7f7Lix4SvEXm73tajRw9s3br1o182Pj4+EAgE+O2336pc9/DwgLa2ttCjKCsrE3ow48aNQ3BwMObPn4/4+Hjo6uoK+509exb29vb44YcfsHTpUkhJSYGIqqzjbdiwocraF5/Px+bNm7FmzRosX74cc+bMqbP39/z5c2H48vz58zAwMBB6df369RPpJqCh8Pl8mJmZ4fvvv8e8efMAADY2Nujfvz+8vb3FOtaTJ08wdOhQpKSk1Ks/n89Henp6raHHtLQ0tGnTBkpKSnj16hV69uwJGxubaqL2rgfYWCxcuBC3bt2CrsMqnHmQifp8g0hIAJZfq2O3fV+xzCk/Px/z58/HxYsXERAQAFNT0zrbICKUlJSIJJKZmZnIzc1Fu3btRBJJDoeDtm3bNuiGg4jw9OnTKuuFN27cQIcOHdCvXz907doVZWVluH//Ps6fP48uXboIvcG30ZTXr19j7dq1CAwMhJOTE8ZMn4NZRx+gnP//v8TCa8dRfOs0KrNTABJAadAUKJtOqzaf1jJS+NttAHrpfHphTyZ8jUx+fj4GDx4MFxcX/PTTT7W29fPzw9WrV7F3717hNSJCp06dEBkZia+//hoA4O3tjeTkZBw9ehRxcXGYMGECoqOjhQv3fD4fK1euxO7duxEYGChcr0tKSsJPP/2E3NxcbN68udZ1vIcPH2LGjBmQlpbGvn37ak0MKSsrw4ULF4ReXV5eHiwtLWFlZYWRI0dCVVVV5PdLnDx69AgmJia4cuUKunTpgqdPn6Jfv37CLwtxQURQUVHB/fv3q63plpeX15gk8u7PGRkZUFFRqdVL09bWRuvWrbF48WL4+/sjJCQEJiYmYnsNorJ//36sXLkSV65cwcsSSUz+MwFllfw62xHnl2ZUVBRcXV0xduxYrF27Fm3btm2wTVHg8/nV1iZrE02BQPBRb/LtNVVVVZHC/jweD3fv3q3iFT569AgGBgbo0KED+Hw+nj59itTUVOH6uaWlJWRkZLBmzRoEZ6pARrfPmzuR/5F9ciN4hVngFWSCX5j5QeET981LU8KErwl48eIFTExMsH37dowfP/6D7cJX1VpJAAAgAElEQVTDw7Fjxw5EREQIryUlJeG7775DcnIyJCQkcOvWLYwYMQI3b95EXl4ehg4dikOHDmHkyJEA3sT0p02bhsrKSgQFBUFTUxMZGRlYunQpTp48CV9fX8ycOVMkr4vP52Pbtm1YuXIlli5dirlz5wq9xsePHwu9uvj4eBgaGgozMI2MjBptjbCubNiwAeHh4YiJiYGkpCSWLVuGhw8f4u+//26w7ZKSEqGAzZs3D3369EGbNm2qiFpeXh40NTVrFTVNTU2R1zaNjY3x6NEj5OfnN2qYrSYuX74MGxsbnD9/XngTNmvDIURmyAPSoocrxRUmKyoqws8//4zIyEjs27evyZKL6stbb1IUkczJyYGSkpJIniSHw4GioqLQmywtLa2WPPP69Wtoa2tDUlISqamp4HA4sBg7HtGth4BHNXuhmcG/oyw54YPCBzROuLopYMLXRFy/fh2WlpY4efIkBgwYUGObpKQkODk54ebNm8JrPj4+KCoqwsaNG8Hn8zFw4EC4urrC2toagwYNwooVK+Dg4ADgTZr7tGnT4OTkBB8fH/B4vCrreEuXLoWSklKd556cnAxHR0fk5+ejd+/eSEhIQHl5uTCMUlt2WXPD5/MxePBgODg4wN3dHaWlpejevTv279+PoUOH1tiHiJCfn1+rl5aamgoulysUr6ysLCgrK2Py5MlVRI3D4YjtJqCgoAAaGhoYMWIETp48KRabopKamor+/fvDz88Po0ePBvBm68ucOXPguec4/K7lgMvj1xr2FGdiRGxsLJydnTF06FBs2rSpXn/XLRk+n4/c3FyRslwzMzNRUVFRqycpLy+PrKwsvHjxAvfu3UNCQgIE+sPQZsD3kPjATYsowlefBKWWQNPeMn7BGBsb48CBA7Czs0N8fDy6dKn+h6KtrY20tLQq144fP46tW7cCAHbs2IHWrVtj4sSJMDc3x6xZs+Dg4ACBQIA1a9Zg27Zt2L9/PywtLXHs2DF4enqiV69e9drDRkS4d++eMHx569YtaGlpITQ0FLNnz8aaNWua3OOoD1JSUvD394epqSmsra3RsWNHLF++HK6urli3bh3S09NrFDVpaelqXlq/fv1gZ2cnvNauXTvhXXZISAj27dsHDw+PRnstcXFxaNeuHUaNGtVoY9REaWkpbG1tMX/+fKHoXbhwAT/88AMiIiLQp08fDO+djz/OP8a5h1mQAMB9JxVeTloSBGCovhrczbs2KLxZWloKb29vHD16FHv27GmULN2WgJSUFNTU1KCmpoYePXp8tH1paSmysrKqCeKrV69w48aNKteys7PRtm1bKOkY1MlTrwkuT4AHr4saZKM5aPnfXJ8R1tbWWL58OaytrXHp0qUq2ZcAoKqqisLCQpSXl0NWVhYvXrxAamoqTExM8OLFC6xYsQLnzp3DxIkTYWpqCi8vL2RnZ8PBwQFFRUVITExEVlYWhg4ditzcXPz555912o9XWFiIM2fOCNOlJSUlYWVlhblz5yIkJAQKCgp48uQJXFxcYGpqioCAABgYGIj7bao3PB5PKGTve2oKCgro3r07BAIBFBUVweVysWzZMpiamkJbWxtDhw6tInIKCgp1Grtv376YNWsWiKhBCQy1ERMTg5KSkiYN6RERXFxcYGBgAE9PTwDArVu3MHHiRPz111/CPae9dJSx274vcorL8e/1VDx4XYRCbiUU5WRgoKmAicY6DQ6HJSQkwNHREX369MGtW7eqfX4+N/h8PrhcLrhcLsrKyqo8inqNz+dDXl4empqaUFZWRseOHVFWVobi4mJkybVB3Vdnq1PIrRSDlaaFhTqbAS8vL1y6dAmnT58WptZnF5fj3/9SsXrXAZiYDYd6e0XkPr0NXnI8Du97c2fbv39/PHz4ULhBPSEhAVOmTMGUKVPg4eEBX19fhIWFibyOR0S4efOm0Ku7fv06Bg0aJAxh6uvr1/glLhAIsGvXLixfvhyLFi3CggULGt3743K5ePXqVa2hx6ysLKipqdW4lqapqYn58+dj1qxZcHd3x71792BmZoY7d+7UqcjAhyAiaGpq4tq1a2JNnHmX7t27Izc3F+np6Y0mru+zatUqhIaGIjY2Fq1bt8bz588xePBgbNy4EZMmTWqSOZSXlws37e/cuRMTJkxoknGBN7/XysrKWsWlrmIk6jUejwc5OTm0bt0acnJyVf5f2zVR2/vdLkfcy/IPvnZRQp3AmyIEmyc1bUWchsKErxkQCASYMmUKJCQk4LXuD+yKfYrYR1kAqlZLkOBXQkpaGvoKPDwL3wPrAT1w+fJlnD59Gn/88QfWr1+PXbt2ITk5WeR1vNzcXJw+fVro1SkoKAiTUszMzOpUDurZs2dwcXFBSUkJAgIChAkPdaWoqOij62mFhYXQ0tL6YIKIjo4ONDQ0ahXgO3fuYOjQofjvv//QsWNHLFy4EHl5efD396/XvN9nzJgxmDFjRq0JTPUlJycHOjo6mDx5MgICAsRuvyaOHz+OOXPm4MqVK9DW1kZWVhYGDx4MDw8PzJ07t0nmcP36dTg6OqJLly7YsmULFBUVxSouH2vP5XIhJSVVJ+ERl0C1atWq0W5wcnNz4bX/DM5kyIIkq35mim5GofzlPXBTboFfmAUZTme04uhB/qsBkP9qYJW2n+oaHxO+ZoLL5WKA/c8o6moBgaRUrUkBJBBAWoIgcSMEkTuWYMGCBcjKyoKjoyPWrVsHQ0NDrF+/vsZ1PIFAgMTERKHQ3blzB2ZmZkKvrqa1xrogEAjg5+eHpUuXYuHChfD09BSKDxEhLy+vVkFLTU0Fj8f7aCq/mpqaWJJEfv/9d8THxyMiIgJFRUUwMDBASEgI+vfv32Dbvr6+KC8vx6pVqxps632Cg4Mxe/ZsbNu2DZMnTxa7/fd5e5MQFhaG/v37o7i4GObm5hg5ciQWL17c6N5PaWkpcnJyUFpaCklJSfD5fLF5OnW5Jisr+0msZYtCSkoKjh8/jtDQUFy7dg1DLEbjwVfTqmV1ZodtRsmdmGr9a/L8WFYno04cSniO38PvV0kC+BgykoTKK0cwWOPNH3FBQQE2b96MYcOGVWmXmZmJ6OhoREREIDo6GhwOR7iB3NTUVKRizx9DIBAIy0Olpqbi1q1bCAgIQGFhIfT09IRZkbKysrV6adra2lBWVm6y0F1lZSX69++PuXPnwtnZGQcPHsT27dtx5cqVBgtreHg4tmzZgtOnT4tptv+Pu7s7/P398fLlS6ioqKC8vLzRPJ3i4mLcuXMH7du3h7S0NLhcLvLz8yEQCMTi/XysfWpqKpYsWQI1NTXs2LEDenp6kJWVbbK/kc8FIsLdu3cRGhqKkJAQvHjxAmPHjoWtrS1GjhwJeXl5uAUm4vT9jBZRhKApYcLXDNx8mQ+LmV7IS4r+YHWEkgfxKIj/C5V5ryDVpj0UjK2hNGAiJPiV4Iavhu98F7i4uEBKSgo8Hg9XrlwRrtU9fvwYw4YNE3p1HTt2rNP8Kisr8fr161o9tfT0dCgrK1cRMG1tbTx58gTHjh0Tbqloidscbt68iREjRuDGjRvQ1NTE4MGDMWPGDMycObNOdng8XhUBSU1NhaWlJaKjo1FeXi7WtZ+UlBQQEVq1aiVMfmoMT0daWhpeXl745ptv4O3tjVatWmHBggXgcrkIDg4We7m3d+Hz+di4cSPWr1+P1atXw8XFhYldHeHz+UhISBCKXWVlJezs7GBra4vBgwdX815vvsxvEUUImhomfM2AW2Ai/lq76IPVEcrT7iM9cBEkWslB/quB4L64CX5RDtpbzoGC0SgM11fFCsuOwvDlmTNn0KlTJ6HQmZiYfHBDdFlZWRURqyn0+G5l/g95aVpaWh/0HFNSUuDm5obMzEzs378fvXpVP75GXBBRvbyfEydOICUlBePHj0dKSgpCQkJga2sLgUAgsg0iqiYgL168QPfu3aGkpCS2RITCwkKYm5sLt2DIyso2WoGAOXPm4Pnz5zhx4gQkJSWxYMECJCYmIjo6ukrhc3Hz6NEjODk5QU5ODv7+/lVK7zFqh8vl4uzZswgNDcWJEyfA4XCEYmdkZPTRm4dDCc+x8tR9lFWKHn361Gt1fh7B60+I7OJyxD7KgurYhQD+lzlVmFmlTUFCMACC8qApUOw/HmXPbyDzyFIUXD4Khd5WiLmfjtAlkzDCdACsra2xdetWaGpqCivznzt37oOi9m5l/reP3bp1E6bza2trQ11dvc7rGnw+XygMkpKS2LZtG44cOQIzMzPY2dlh/PjxwvRscYbnysvLISMjU2dP55tvvsGtW7fw+PFjDBw4ECkpKcjMzISLi4vIAlXTzcWECRPw3XffiXUdLigoCPLy8rCxsWlU8dm9ezfOnj2LhIQESElJYd26dTh9+jTi4uIabVyBQIAdO3ZgxYoVWLZsWb1qw36JFBQU4NSpUwgJCUF0dDR69eoFW1tbeHl51Xnd/q14rTz1oEmLEDQnTPiamH//S/1om4qMJwCAVppvDoGV1XjzyC/MhIBbDBnZ1jB1XAT59EQcPnwYa9euRVpaGvh8PnR0dKClpQUOhwM1NTVoaGjg66+/hpKSEhQVFSErK1slY+2tgNy9exf//fdfvUNxfD6/RrHo2LEjQkNDcfToURgbG0NDQ6NGIVFRUalXeE5OTq7eX5T29vYYNWoUtm3bBkdHR3Tv3h09evRokIfar18/XLt2TazCFxkZiZKSEgwaNEhsNt8nNjYWy5cvR3x8PJSUlLB//37haR+NdcDu8+fP4ezsjPLycly6dKlJDz3+FHn16hVOnDiBkJAQXL58GWZmZrC1tcWOHTvA4XAaZNt+gC566Sg3SRGClgATvibmQXphlS0LNcEvyQcASLRq/b9HuXeey4OkXFtcS05D5YVwCAQCVFZWgsfjgcvl4tmzZ0hPT6930kH79u3rFZ6TkZH5YEiFiBAYGIiff/4ZZmZmWLp0aYs4FNTY2Biurq6YPXs2QkJC4Ovri7lz5+L8+fP1Xlvq27cvVqxYIdZ5RkVFwdjYuNG8rmfPnmHSpEk4dOgQunXrhvDwcPzyyy84f/58lcNLxQURYe/evfD29hbuA22KEzs+RR4+fIiQkBCEhobi0aNHsLa2hqurK4KDg8VejLspihC0FJjwNTGFXN5H20i1UQa/MAtUUQYAwsc3z725+x5kPgKr1syo5v20xC8QCQkJTJ8+HSNGjMCsWbPQt29fBAQE1HjSfFOzbNkyGBsb48iRI3Bzc4Ofnx+OHDmCKVOm1Mtenz59kJSUBD6fL5bfxYsXL1BYWAhbW9sG26qJ4uJi2NjYYPHixRg5ciQuX74MZ2dnnDx5slGq8qSlpWHmzJnIysrC+fPnRSrH9SUhEAhw7do1hIaGIjQ0VPi7X7FiBczMzJrkhlGlrewnty+vrrBgehOjKPfxe41WnDcHwJa/fvS/x2QAgJSiGiTl3tzlaau1R9euXaGtrQ0VFRW0adOmRYreu2hpaeH48ePw8vKCtbU1lixZgvLyD1eOaApkZWWxf/9+/Pjjj8jOzsaOHTvg6emJ4uLietlr164d1NXV8fDhQ7HM79y5c5CSkoKFhYVY7L2LQCDA9OnT0a9fP8ybNw/37t2DnZ0dDh48KJZ9je/y1uvv3bs3Bg4ciMuXLzPR+x8VFRWIjo6Gu7s7OnToAGdnZ0hISODAgQN4+fIldu7ciZEjR7aIKMnnAvP4mhgDDUXISqcj+78IlL+8J1zPK01OAK8gE/JfDYDigAkoe3wVBfFBqMx6Ae7zGwAApQHfAQAkBDzwc1NQUfH1J/dhkJCQwLRp0zB8+HDMnj0bxsbG2L9/P/r16/fxzo1Ev3794OTkBA8PDxw9ehRDhw7FypUrsXr16nrbu3btWr0r2bzL21MYDA0NG2zrfXx9fZGZmYmgoCCkpqZi1KhRWL9+vdiLYGdkZOCHH37AkydPEBUVhd69e4vV/qdIUVERIiMjERoaioiICOjr68PW1hZnz56Fvr5+c0/v84cYTUpWEZe+WnqK2vQcTgCq/VMaNIU6/RJGqjaLSEalA0FSmqQU1UjZzJE6ep2kTr+Ekd7ik2Qy1IJUVVVp9uzZdOnSJRIIBM390uqMQCCgoKAg4nA45OXlRWVlZc02l7KyMjIwMKB//vmHXr16RSoqKvTw4cN62dq4cSN5eHg0eE4CgYDatWtHo0ePbrCt9/nnn3+oY8eOlJ6eTjk5OdS9e3fasGGD2Mc5evQoqaur0+LFi4nL5Yrd/qdEeno6/fnnnzR69GhSUFAgS0tL2rVrF7169aq5p/bFwfbxNQPiqpbw7Nkz/PXXXwgMDASPx4O9vT3s7e3rfARRc5ORkYE5c+bg7t27CAgI+OB5hY3N5cuXMX78eNy6dQsHDhzA2bNnER4eXudEl7i4OHh6eiIhIaFB80lOToahoSG2b98OFxeXBtl6l6SkJFhYWCA6Ohr6+voYMWIEBg0ahPXr14ttjJycHHh4eOD69euNEjr9VHjy5Ilwve727dsYNWoUbG1tYWVl9dmdIfgpwdb4moE55l0hJ12/9Tg5aSm4m78Rts6dO2PJkiW4f/8+goKCkJeXh0GDBsHExAS7du1CTk6OOKfdaKirq+Pff//Fb7/9BltbW3h6eqKsrOzjHcXMwIEDMXXqVMybNw/z5s3D06dPERYWVmc7vXv3xu3bt1FZ2bDjWs6cOQOBQICRI0c2yM67ZGRkwNbWFn/88Qd69uyJ77//Hl27dsXatWvFNkZYWBh69eoFDQ0NJCUlfVGiR0S4fv06li1bhm+++QaDBg3Co0eP4O3tjYyMDBw5cgSTJ09motfMMI+vmWisagmVlZWIjo7GoUOHEBERAXNzczg4OGD06NGNWm5KXGRlZcHDwwM3btxAQEAATExMmnT80tJSGBkZYe3atWjTpg1mz56Nu3fv1vm969mzpzCZo75YWlri5s2bSE9Pr7eNdykvL8ewYcMwfPhw+Pr6YsaMGcjIyMDx48c/WOmnLhQUFODHH39EbGws9u/fjyFDhohh1i0fHo+HuLg4oWfXqlUrYeWU/v37t/iksy8R5vE1E/YDdLHEujtay0jhY5E0CYk3dfFEKREkIyOD0aNHIygoCCkpKbCxscHOnTuhra0NNzc3xMXFQSAQXWybGjU1Nfz9999YtWoVJkyYgAULFqC0tLTJxpeXl8e+ffswZ84c9OnTB4aGhtiwYUOd7fTt2xeJiYn1ngcR4eLFi2LL5iQiuLu7g8PhwMfHB97e3rh37x6OHj0qFtE7c+YMevXqBTk5Ody6deuzF73S0lKEhobC0dERGhoa8PT0BIfDwalTp/Do0SOsW7cOJiYmTPRaKMzja2ZupeY3SbWEly9fCtcDS0pKMG3aNDg4OLToDLLs7GzMnz8fV69ehb+/P0xNTZts7Pnz5yM3NxcrVqxAnz59cP36dXTq1Enk/jt37sTNmzfh5+dXr/Hv3LmDb7/9FkFBQbCxsamXjXfZtm0b9u7di0uXLmHv3r3YvXs34uPjoaqq2iC7xcXFWLRoEcLCwrB3795G2XbRUsjJyUFYWBhCQkJw9uxZfPvtt7C1tYWNjU2jHT7MaCSaLa2GUYXsIi7tjn1MPx5John7r9KPR5Jod+xjyi4SbyacQCCgpKQkWrBgAWloaFDfvn1p69atlJGRIdZxxElISAhpamrSvHnzqLi4uEnGLC4uJj09PTp58iT5+PjQxIkT69Q/ISGBevfuXe/xN27cSNLS0pSfn19vG2+Jjo4mDQ0NevbsGR0+fJh0dHTo+fPnDbZ74cIF0tPTI0dHR8rLy2uwvZbI8+fPacuWLWRubk6Kioo0fvx4OnjwIOXk5DT31BgNgAnfF0xlZSVFRUWRvb09KSkpkbW1NQUFBVFJSUlzT60aOTk5ZG9vT3p6enTu3LkmGfPcuXOkra1NaWlppKurS2fOnBG5b1lZGbVu3breWzRMTEyoW7du9er7Lo8ePSIOh0Pnz5+nqKgo4nA4dPv27QbZLC0tpZ9++om0tLTo+PHjDZ5jS0IgENDNmzfJ19eXevfuTaqqquTs7EzHjx+n0tLS5p4eQ0ww4WMQEVFRUREdPHiQLCwsSFlZmZycnCgmJob4fH5zT60KJ06cIG1tbXJ3d6eioqJGH8/d3Z2cnJzo2LFj1L17d6qoqBC5b+/evSkhIaHOY/J4PJKTk6MFCxbUue+75Ofnk4GBAe3evZuuXr1KqqqqFBcX1yCbV65cIX19fZo0aRJlZ2c3yFZLgcfj0YULF2jBggWkp6dHnTp1oh9//JHOnz9PlZWVzT09RiPAhI9RjbS0NNqwYQMZGRmRjo4OLVq0qMFegjjJzc0lJycn0tXVpZiYmEYdq6ioiHR1dSk8PJwsLCxo06ZNIvd1c3Oj7du313nM//77j2RlZSk+Pr7Ofd/C4/HI2tqa3N3d6eHDh6ShodEg74zL5ZK3tzepq6vT33//XW87LYWysjI6efIkubi4kJqaGhkaGtLy5cspKSnpkywGwagbTPgYtXL79m1atGgRaWtrk5GREW3YsKHFVJoIDw8nHR0d+uGHH6igoKDRxjl9+jR16NCBrl69SioqKvT69WuR+vn5+dH06dPrPN7y5ctJRkamTt7l+yxatIjMzc3p+fPnpKurS3v37q23raSkJOrVqxeNGzdO5NfeEsnLy6NDhw7RxIkTSVFRkYYMGUKbNm2ip0+fNvfUGE0MEz6GSPB4PIqJiSEnJydSVlYmCwsLCgwMbJJwY23k5+eTi4sLderUiaKjoxttHFdXV3J1dSVPT09ydHQUqU9SUhJ9/fXXdR7L0NCQ+vTpU+d+bwkMDCQ9PT16/Pgx9erVi1auXFkvOxUVFfTbb7+RmpoaHThw4JP0hFJTU2nnzp00cuRIUlBQoLFjx9K+ffsoMzOzuafGaEaY8DHqTElJCQUFBZG1tTUpKSmRvb09RUVFEY/Ha7Y5RUZGUocOHcjV1VUsmZDvU1BQQB07dqTQ0FDS0tKiS5cufbRPRUUFycvLU2FhocjjVFRUkIyMDK1evbpe87xy5QqpqalRYmIiDRkyhObOnVsvwbp79y717duXLCws6OXLl/WaS3MgEAjo3r17tGrVKvr222+pXbt2ZG9vT8HBwc1+k8ZoOTDhYzSI9PR02rp1K/Xt25c0NTVpwYIFzbZOUlBQQG5ubtShQweKiIgQu/3IyEjq1KkT+fn5kbGxsUhCP2DAAIqNjRV5jIsXL5KMjAzdv3+/zvNLTU0lbW1tOnbsGNnZ2dH3339f5+QkHo9H69evJ1VVVdqzZ88n4eXx+Xy6fPkyeXl50VdffUU6Ojrk4eFBZ86caVC4mPH5wjawM8TGgwcPcOjQIRw6dAht27aFg4MDpk2bBh0dnSadx5kzZzBz5kwMGzYMmzZtgrJy/Tf+v8+MGTMgKyuLO3fuwMHBAW5ubrW2nzt3LnR1dbFw4UKR7P/444/Yt28fCgsL61Qcu6ysDGZmZrCxsUFKSgqePHmC8PBwyMqKfmL248eP4eTkBGlpafj7+0NPT0/kvk1NRUUFzp07h5CQEBw/fhzt27cXlgnr06dPnQuLM74wmlt5GZ8ffD6fLly4QK6urtS+fXsaNmwY+fv7N2oCyvsUFhbS7NmzSUdHh8LCwsRmNy8vj3R0dGjPnj3E4XA+upH5wIEDNHnyZJHtf/XVVzRixIg6zUkgENC0adNo0qRJ9Ouvv1KfPn3qFF7l8/m0fft2UlVVpS1btrS4LSxvKSgooL///psmT55MysrKNHDgQFq3bl29j49ifLkw4WM0KmVlZfTvv/+SjY0NKSkp0eTJkyksLKzJQlAxMTHUuXNncnR0pNzcXLHYDAsLo86dO5Orqyu5u7vX2vbevXvUpUsXkeyWlZWRlJRUnTMw165dS8bGxrR582bq2rVrnarwPH/+nIYNG0YDBgygBw8e1GncpuD169e0Z88esrKyIgUFBbKysqI9e/a0mMxixqcJEz5Gk5GdnU07d+6kgQMHEofDoXnz5tHVq1cbfR2pqKiIPDw8xFppxMHBgVxdXYnD4VBSUtIH2/F4PFJQUBBJdE+fPk2SkpJ1Eq6wsDDS0tKiXbt2kZaWFj158kSkfgKBgPbu3Uuqqqq0Zs2aZk1Mep/k5GRat24dmZiYkLKyMk2ePJmOHDnSpBEDxucNEz5Gs5CcnEzLly+nLl26kL6+Pv3+++/07NmzRh3z/Pnz1KVLF5o2bVqDq47k5OSQlpYWLVy4kAYPHlyreJuZmYm01cLZ2Zk4HI7Ic7h37x6pqanR9u3bSU1NrVYBfpe0tDSytram3r17t4jCBAKBgK5du0ZLliyhHj16kIaGBv3www8UERHxxZ/azmgcmPAxmhWBQECXLl2i2bNnk4qKCpmampKfn5/YwpLvU1xcTPPnzydNTU0KCQlpkK3Q0FDq0qULGRkZ0aFDhz7YbuHChbRq1aqP2uvYsaPIxbBzcnKoa9eu5OvrS2pqanT27NmP9hEIBHTo0CHicDi0fPnyZs14rKiooDNnzpCHhwfp6OhQt27daNGiRXTp0qUWu8bI+HxgwsdoMZSXl1NoaChNmDCBFBUVacKECRQaGkrl5eViHysuLo66detGkydPpqysrHrbmTJlCk2aNIm0tLQ+mFBy5MgRsrOzq9VOcXExSUpKihSKrayspBEjRtCMGTNIS0uLjh49+tE+GRkZNH78eOrRowclJiZ+tH1jUFxcTMHBweTg4EDt27enfv360cqVK+nevXufxLYJxucDEz5GiyQ3N5f8/PzI1NSUVFRUaPbs2XTp0iWxfkGWlJQIj2cSRTxqIisrizQ0NGjUqFHk6elZY5vHjx9Thw4darVz7NgxkpSUFOkEgHnz5pG5uTl17dqV/vjjj4+2Dw4OJg0NDfLy8mry0GFmZib5+/vTuHHjSEFBgUaMGEE7duz4pEqRZx8AAAqxSURBVDbFMz4/mPAxWjxPnz6l33//nfT19alLly60fPlySk5OFpv9ixcvkr6+Pn333Xf1Opfw6NGj1KVLF1JRUakxM1IgEFC7du0oPT39gzbGjx9PnTt3/uhYf/75J3Xt2pUMDQ1p2bJltbbNycmhqVOnUrdu3USqNCMunj59Sps3b6YhQ4YIPffAwMBGC18zGHWFCR/jk0EgENDVq1dp3rx5xOFwaMCAAbRz506xHI9TWlpKnp6ewtMH6upZfvfdd2Rubk4WFhY19h05cmSt+wk5HA65ubnVOkZcXBypqqrSwIEDyc3NrdY5hoeHk7a2Ns2bN6/Rz1cUCAR048YN8vHxIUNDQ1JTU6MZM2bQyZMn2Rl2jBYJEz7GJ0lFRQWFhYXR5MmTSVFRkWxsbOjo0aP1Pvj1LQkJCdS9e3caP358rR7a+2RkZBCHwyFdXd0ak2a8vb1p+fLlNfbNz88nCQkJunz58gftv3jxgtTV1cnU1JTGjx//we0HBQUF5OLiQrq6uo16YC+Px6PY2Fj68ccfSVdXlzp37kwLFiygCxcutKitEQxGTTDhY3zyFBQUkL+/Pw0dOpTat29Prq6uFBsbW+/swLKyMvrll1+Iw+HQX3/9JbL3FxQURB07dqROnTpV83SOHTtGo0ePrrHfvn37SEZG5oPzLS4uJkNDQxo0aBANGTLkg+J+5swZ6tSpE7m5udWpcouolJaW0vHjx8nZ2ZlUVVXJyMiIfH196ebNmyw5hfFJwYSP8VmRkpJCa9asoR49elCnTp1oyZIl9Sr4TER09epV6tGjB9nY2IhUKUQgEJCtrS3p6+uTj49PledevnxJHA7ng2HQnj17ftDmxIkTqXfv3tSrVy/Ky8ur1qa4uJjmzJlDOjo6Yi/OnZubSwcPHqTx48eToqIimZub05YtWxp9zyWD0Zgw4WN8lggEAkpKShJmbfbt25e2bt1a5+QVLpdLS5YsIQ6HQwcPHvyoZ/P69WtSUVEhJSWlKuIgEAhIXV2dUlJSqvVRVlamX375pUZ7vr6+pKenR506daK0tLRqz8fHx1PXrl3JwcFBbMkjKSkptH37dho+fDgpKCiQjY0NBQQENGjbB4PRkmDCx/jsqayspKioKLK3tyclJSWytramoKCgOiV9JCYm0jfffENjxoypUYDeJTAwkDgcDtna2la5PmbMGAoODq5yLSMjgyQkJOjx48fV7AQHB5OKigpxOJxqhZjLysro559/Jk1NTQoNDRX5ddSEQCCgO3fu0O+//059+/al9u3b0/Tp0+nYsWNUXFzcINsMRkuECR/ji6KoqIgCAwPJwsKClJWVycnJiWJiYkRaDywvL6dly5aRmpoa7d+//4Pen0AgICsrK2rXrl2VUmU+Pj60ePHiKm3XrVtH8vLy1WzcuHGDlJSUSFlZma5evVrluatXr1L37t1p4sSJ9fbC+Hw+Xbx4kTw9Palbt27UoUMHmjt3LsXExLAz7BifPUz4GF8sr169oo0bN5KRkRHp6OjQokWLRKpdmZSURIaGhmRlZfXBjdipqamkqKhInTt3FlaeCQ8Pr3bk0MCBA8nExKTKtczMTNLS0iJFRUWKiooSXi8vL6elS5cSh8OhoKCgOieUcLlcOnXqFLm5uZG6ujr17NmTli5dSomJiSw5hfFFwYSPwSCi27dvk5eXF+no6JCRkRFt2LCh1oSWiooK8vX1JVVVVdq7d2+NwuHv708KCgq0du1aInoT1lRWVq7SVl5enjZu3Cj8uby8nL799ltSUFCgw4cPC6/fvHmTDA0NacyYMXU6kic/P5+CgoJo0qRJpKSkRIMGDaL169eLtQAAg/GpwYSPwXgHHo9HMTEx5OzsTMrKymRhYUGBgYFUVFRUY/ubN2+SsbExWVhY0IsXL6o8JxAIaMiQISQvL0+vXr2irCIudbScQTP+jCXn/Vdpxp8XSLH/eHqcmiFsP336dGrTpg1t3ryZiN6sT65cuZLU1NQoICBAJM/s1atXtHv3brK0tCQFBQWytrYmPz+/Ou1LZDA+ZySIiJr7FHgGoyVSWlqKEydOIDAwEBcvXsTYsWNhb2+P4cOHQ1paWtiusrIS69evx+bNm7Fq1SrMnDkTEhISAICXL1+ixxBrdLJ2Q0X7rqioqABJ/n9f4pVDTq41zPXVoJx2Fdt9f8asWbOwadMmPHjwAI6OjlBUVIS/vz86dOjwwbk+evQIoaGhCAkJwYMHD2BlZQVbW1tYWVlBQUGh8d4kBuMThAkfgyECmZmZOHLkCAIDA5GWloYpU6bA3t4eRkZGQpG7c+cOnJ2doaysjD///BO6uro4lPAcPiduo5IPSEhKftC+BAB+JRed864jZo8vtm3bhtWrV+O3337DrFmzhGO8RSAQ4L///hOKXX5+PmxsbGBnZwdzc3O0atWqMd8OBuOThgkfg1FHHjx4gEOHDuHQoUNo27YtHBwcMHXqVHTo0AE8Hg8bNmzAhg0bMH7RJlwoVgO3UiCybVkpCcg/jIRCxg0EBASgS5cuwucqKysRGxuLkJAQHD9+HG3atIGdnR3s7OzQr18/SNYirAwG4/9hwsdg1BOBQICLFy8iMDAQ//77L4yMjODg4IAJEybg7I0nmOGzHcV3zqEyOwUgAZQGTYGy6TQAQEXGU+Sd3Yvy18mgijJIKXKg4+4PAJCGAP/OHgyjju1QXFyMqKgohISE4NSpU+jWrRvs7Oxga2sLAwOD5nz5DMYnCxM+BkMMcLlchIeHIzAwEOfOnYOe4xokn/0HvMJs8AoywS/MrCJ8pclXkB97AJJyCihPvVtF+CQA6LfhQubKfsTGxmLgwIGwtbXFuHHjoK2t3YyvksH4PGDCx2CImeSUdIzalQg+3qzLZQb/jrLkhCrC95bSR5eRdWxlFeEDAAkBD4t7lOL7cVZQVlZu0vkzGJ870h9vwmAw6kLMsxJIS0uBzxN9be99ZFu1Aun2ZKLHYDQCbDWcwRAzD9ILUd4A0QMALk+AB6+LxDQjBoPxLkz4GAwxU8jliclOpVjsMBiMqjDhYzDEjKKceFYQFOVkxGKHwWBUha3xMRhixkBDEbLS6cj+LwLlL++hIuMJAKA0OQG8gkzIfzUAMio6KLj8L3iFWQAAQVkhssM2Q0peEe2GuUBOWhIGmqziCoPRGDCPj8EQMxP76AAAyl/eQ8mdGPD/J26Vmc9QcicGFRlPwS/OQ8mdGJSn3AIAUCUXJXdiUPLg4pufAUw01mmW+TMYnztsOwOD0Qi4BSbi9P0M1OfTJSEBWH6tjt32fcU/MQaDwTw+BqMxmGPeFXLSUvXqKyctBXfzrmKeEYPBeAsTPgajETDsoIwl1gZoLVO3j1hrGUkssTZALx22f4/BaCxYcguD0UjYD9AFAKw89QBcHr/WsKeExBtPb4m1gbAfg8FoHNgaH4PRyNxKzccf5x/j3MMsSODN5vS3yElLggAM1VeDu3lX5ukxGE0AEz4Go4nIKS7Hv9dT8eB1EQq5lVCUk4GBpgImGutApa1sc0+PwfhiYMLHYDAYjC8KltzCYDAYjC8KJnwMBoPB+KJgwsdgMBiMLwomfAwGg8H4omDCx2AwGIwvCiZ8DAaDwfiiYMLHYDAYjC8KJnwMBoPB+KJgwsdgMBiML4r/AzF1wwWWWst0AAAAAElFTkSuQmCC"
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "source": [
    "Sz=[[1,0],[0,-1]]\n",
    "Si=[[1,0],[0,1]]\n",
    "def addzz(t1,t2):\n",
    "    u=1\n",
    "    for ii in range(n):\n",
    "        if ii==t1 or ii==t2:\n",
    "            u=np.kron(u,Sz)\n",
    "        else:\n",
    "            u=np.kron(u,Si)\n",
    "    return u"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "cf=0\n",
    "for i,j in list(g.edges):\n",
    "    if cipher[i]==cipher[j]:\n",
    "        cf=cf-addzz(i,j)\n",
    "    else:\n",
    "        cf=cf+addzz(i,j)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "source": [
    "def sortdis(M,C):\n",
    "    P=np.abs(M)**2\n",
    "    for i in range(n):\n",
    "        basis=np.zeros((1,n))\n",
    "        basis[i]=1\n",
    "        PP=np.real(np.dot(np.dot(basis,C),basis.T))\n",
    "    index= np.array(PP).argsort()\n",
    "    P=P[index]\n",
    "    return P"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "from qiskit import QuantumCircuit, assemble, Aer\n",
    "from math import pi, sqrt\n",
    "from qiskit.visualization import plot_bloch_multivector, plot_histogram\n",
    "sim = Aer.get_backend('aer_simulator')"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "source": [
    "def costfunction(x):\n",
    "    qc = QuantumCircuit(12)\n",
    "    initial_state = [1,0]\n",
    "    for qubit in range(12):\n",
    "        qc.initialize(initial_state, qubit)\n",
    "    for qubit in range(12):\n",
    "        qc.h(qubit)\n",
    "    for qubit in range(12):\n",
    "        qc.ryy(x[qubit],qubit,np.mod(qubit+1,12)+int((qubit+1)/12))\n",
    "    for qubit in range(12):\n",
    "        qc.rx(x[qubit+12],qubit)\n",
    "    qc.save_statevector()\n",
    "    qobj = assemble(qc)\n",
    "    state = sim.run(qobj).result().get_statevector()\n",
    "    ampli=np.abs(state)\n",
    "    state1=ampli*Ss\n",
    "    state2=np.sum(state1,1)\n",
    "    state3=state2/np.sqrt(np.sum(np.abs(state2)**2))\n",
    "    ff=np.real(np.dot(np.dot(state3,cf),state3.T))\n",
    "    return ff"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "source": [
    "para=np.ones(24)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "source": [
    "output=NM(costfunction,para,0.1)\n",
    "print(output)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "(array([1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  ,\n",
      "       1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.  , 1.05,\n",
      "       1.  , 1.  ]), -0.5832608081464086, 25)\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "shijinzhi=1\n",
    "for i in range(n):\n",
    "    shijinzhi=shijinzhi+cipher[i]*2**(n-i-1)\n",
    "qcipher=np.zeros((2**n),1)\n",
    "qcipher[shijinzhi]=1\n",
    "qc = QuantumCircuit(12)\n",
    "    initial_state = [1,0]\n",
    "    for qubit in range(12):\n",
    "        qc.initialize(initial_state, qubit)\n",
    "    for qubit in range(12):\n",
    "        qc.h(qubit)\n",
    "    for qubit in range(12):\n",
    "        qc.ryy(x[qubit],qubit,np.mod(qubit+1,12)+int((qubit+1)/12))\n",
    "    for qubit in range(12):\n",
    "        qc.rx(x[qubit+12],qubit)\n",
    "    qc.save_statevector()\n",
    "    qobj = assemble(qc)\n",
    "    state = sim.run(qobj).result().get_statevector()"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "source": [
    "x=np.zeros(24)\n",
    "costfunction(x)"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "-0.1927710843373493"
      ]
     },
     "metadata": {},
     "execution_count": 15
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "source": [
    "m=np.eye(3)\n",
    "m=np.sum(m,0)\n",
    "m"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "array([1., 1., 1.])"
      ]
     },
     "metadata": {},
     "execution_count": 12
    }
   ],
   "metadata": {}
  }
 ]
}